Word Model¶
Installation and set up¶
In [3]:
Copied!
!pip install lavague
import os
# Check if running in Google Colab
try:
from google.colab import userdata
IN_COLAB = True
except ImportError:
IN_COLAB = False
if IN_COLAB:
os.environ["OPENAI_API_KEY"] = userdata.get('OPENAI_API_KEY')
else:
os.environ["OPENAI_API_KEY"] = os.getenv('OPENAI_API_KEY')
!pip install lavague
import os
# Check if running in Google Colab
try:
from google.colab import userdata
IN_COLAB = True
except ImportError:
IN_COLAB = False
if IN_COLAB:
os.environ["OPENAI_API_KEY"] = userdata.get('OPENAI_API_KEY')
else:
os.environ["OPENAI_API_KEY"] = os.getenv('OPENAI_API_KEY')
Collecting lavague Using cached lavague-1.1.19-py3-none-any.whl.metadata (8.6 kB) Collecting lavague-contexts-openai<0.3.0,>=0.2.0 (from lavague) Using cached lavague_contexts_openai-0.2.4-py3-none-any.whl.metadata (1.5 kB) Collecting lavague-core<0.3.0,>=0.2.31 (from lavague) Using cached lavague_core-0.2.32-py3-none-any.whl.metadata (1.5 kB) Collecting lavague-drivers-selenium<0.3.0,>=0.2.12 (from lavague) Using cached lavague_drivers_selenium-0.2.12-py3-none-any.whl.metadata (1.2 kB) Collecting lavague-gradio<0.3.0,>=0.2.8 (from lavague) Using cached lavague_gradio-0.2.8-py3-none-any.whl.metadata (1.1 kB) Collecting llama-index-embeddings-azure-openai==0.1.11 (from lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached llama_index_embeddings_azure_openai-0.1.11-py3-none-any.whl.metadata (804 bytes) Collecting llama-index-embeddings-openai<0.2.0,>=0.1.9 (from lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached llama_index_embeddings_openai-0.1.11-py3-none-any.whl.metadata (655 bytes) Collecting llama-index-llms-azure-openai==0.1.10 (from lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached llama_index_llms_azure_openai-0.1.10-py3-none-any.whl.metadata (787 bytes) Collecting llama-index-llms-openai<0.2.0,>=0.1.9 (from lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached llama_index_llms_openai-0.1.27-py3-none-any.whl.metadata (610 bytes) Collecting llama-index-multi-modal-llms-azure-openai==0.1.4 (from lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached llama_index_multi_modal_llms_azure_openai-0.1.4-py3-none-any.whl.metadata (820 bytes) Collecting llama-index-multi-modal-llms-openai<0.2.0,>=0.1.6 (from lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached llama_index_multi_modal_llms_openai-0.1.8-py3-none-any.whl.metadata (728 bytes) Collecting llama-index-core<0.11.0,>=0.10.11.post1 (from llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached llama_index_core-0.10.61-py3-none-any.whl.metadata (2.4 kB) Collecting azure-identity<2.0.0,>=1.15.0 (from llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached azure_identity-1.17.1-py3-none-any.whl.metadata (79 kB) Collecting httpx (from llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached httpx-0.27.0-py3-none-any.whl.metadata (7.2 kB) Requirement already satisfied: PyYAML>=5.3 in /usr/local/lib/python3.10/dist-packages (from lavague-core<0.3.0,>=0.2.31->lavague) (6.0.1) Requirement already satisfied: ipython<8.0.0,>=7.34.0 in /usr/local/lib/python3.10/dist-packages (from lavague-core<0.3.0,>=0.2.31->lavague) (7.34.0) Requirement already satisfied: jsonschema<5.0.0,>=4.23.0 in /usr/local/lib/python3.10/dist-packages (from lavague-core<0.3.0,>=0.2.31->lavague) (4.23.0) Collecting langchain<0.2.0,>=0.1.20 (from lavague-core<0.3.0,>=0.2.31->lavague) Using cached langchain-0.1.20-py3-none-any.whl.metadata (13 kB) Collecting llama-index==0.10.56 (from lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index-0.10.56-py3-none-any.whl.metadata (11 kB) Collecting llama-index-retrievers-bm25<0.2.0,>=0.1.3 (from lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_retrievers_bm25-0.1.5-py3-none-any.whl.metadata (700 bytes) Collecting lxml<6.0.0,>=5.1.1 (from lavague-core<0.3.0,>=0.2.31->lavague) Using cached lxml-5.2.2-cp310-cp310-manylinux_2_28_x86_64.whl.metadata (3.4 kB) Collecting lxml-html-clean<0.2.0,>=0.1.1 (from lavague-core<0.3.0,>=0.2.31->lavague) Using cached lxml_html_clean-0.1.1-py3-none-any.whl.metadata (1.5 kB) Requirement already satisfied: msgpack<2.0.0,>=1.0.8 in /usr/local/lib/python3.10/dist-packages (from lavague-core<0.3.0,>=0.2.31->lavague) (1.0.8) Collecting seaborn<0.14.0,>=0.13.2 (from lavague-core<0.3.0,>=0.2.31->lavague) Using cached seaborn-0.13.2-py3-none-any.whl.metadata (5.4 kB) Collecting tenacity<8.4.0,>=8.2.0 (from lavague-core<0.3.0,>=0.2.31->lavague) Using cached tenacity-8.3.0-py3-none-any.whl.metadata (1.2 kB) Collecting trafilatura<2.0.0,>=1.9.0 (from lavague-core<0.3.0,>=0.2.31->lavague) Using cached trafilatura-1.12.0-py3-none-any.whl.metadata (14 kB) Collecting llama-index-agent-openai<0.3.0,>=0.1.4 (from llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_agent_openai-0.2.9-py3-none-any.whl.metadata (729 bytes) Collecting llama-index-cli<0.2.0,>=0.1.2 (from llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_cli-0.1.13-py3-none-any.whl.metadata (1.5 kB) Collecting llama-index-core<0.11.0,>=0.10.11.post1 (from llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached llama_index_core-0.10.56-py3-none-any.whl.metadata (2.5 kB) Collecting llama-index-indices-managed-llama-cloud>=0.2.0 (from llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_indices_managed_llama_cloud-0.2.7-py3-none-any.whl.metadata (3.8 kB) Collecting llama-index-legacy<0.10.0,>=0.9.48 (from llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_legacy-0.9.48-py3-none-any.whl.metadata (8.5 kB) Collecting llama-index-program-openai<0.2.0,>=0.1.3 (from llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_program_openai-0.1.7-py3-none-any.whl.metadata (760 bytes) Collecting llama-index-question-gen-openai<0.2.0,>=0.1.2 (from llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_question_gen_openai-0.1.3-py3-none-any.whl.metadata (785 bytes) Collecting llama-index-readers-file<0.2.0,>=0.1.4 (from llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_readers_file-0.1.32-py3-none-any.whl.metadata (5.4 kB) Collecting llama-index-readers-llama-parse>=0.1.2 (from llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_readers_llama_parse-0.1.6-py3-none-any.whl.metadata (3.6 kB) Requirement already satisfied: SQLAlchemy>=1.4.49 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy[asyncio]>=1.4.49->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (2.0.31) Requirement already satisfied: aiohttp<4.0.0,>=3.8.6 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (3.10.0) Collecting dataclasses-json (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached dataclasses_json-0.6.7-py3-none-any.whl.metadata (25 kB) Collecting deprecated>=1.2.9.3 (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached Deprecated-1.2.14-py2.py3-none-any.whl.metadata (5.4 kB) Collecting dirtyjson<2.0.0,>=1.0.8 (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached dirtyjson-1.0.8-py3-none-any.whl.metadata (11 kB) Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (2024.6.1) Requirement already satisfied: nest-asyncio<2.0.0,>=1.5.8 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.6.0) Requirement already satisfied: networkx>=3.0 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (3.3) Requirement already satisfied: nltk<4.0.0,>=3.8.1 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (3.8.1) Requirement already satisfied: numpy<2.0.0 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.26.4) Collecting openai>=1.1.0 (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached openai-1.39.0-py3-none-any.whl.metadata (22 kB) Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (2.1.4) Requirement already satisfied: pillow>=9.0.0 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (9.4.0) Requirement already satisfied: requests>=2.31.0 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (2.31.0) Collecting tiktoken>=0.3.3 (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached tiktoken-0.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.6 kB) Requirement already satisfied: tqdm<5.0.0,>=4.66.1 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (4.66.4) Requirement already satisfied: typing-extensions>=4.5.0 in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (4.12.2) Collecting typing-inspect>=0.8.0 (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached typing_inspect-0.9.0-py3-none-any.whl.metadata (1.5 kB) Requirement already satisfied: wrapt in /usr/local/lib/python3.10/dist-packages (from llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.16.0) Collecting selenium<5.0.0,>=4.18.1 (from lavague-drivers-selenium<0.3.0,>=0.2.12->lavague) Using cached selenium-4.23.1-py3-none-any.whl.metadata (7.1 kB) Collecting gradio==4.39.0 (from lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached gradio-4.39.0-py3-none-any.whl.metadata (15 kB) Collecting aiofiles<24.0,>=22.0 (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached aiofiles-23.2.1-py3-none-any.whl.metadata (9.7 kB) Requirement already satisfied: anyio<5.0,>=3.0 in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (3.7.1) Collecting fastapi (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached fastapi-0.112.0-py3-none-any.whl.metadata (27 kB) Collecting ffmpy (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached ffmpy-0.4.0-py3-none-any.whl.metadata (2.9 kB) Collecting gradio-client==1.1.1 (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached gradio_client-1.1.1-py3-none-any.whl.metadata (7.1 kB) Requirement already satisfied: huggingface-hub>=0.19.3 in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (0.23.5) Requirement already satisfied: importlib-resources<7.0,>=1.3 in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (6.4.0) Requirement already satisfied: jinja2<4.0 in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (3.1.4) Requirement already satisfied: markupsafe~=2.0 in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (2.1.5) Requirement already satisfied: matplotlib~=3.0 in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (3.7.1) Collecting orjson~=3.0 (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached orjson-3.10.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (50 kB) Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (24.1) Requirement already satisfied: pydantic>=2.0 in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (2.8.2) Collecting pydub (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached pydub-0.25.1-py2.py3-none-any.whl.metadata (1.4 kB) Collecting python-multipart>=0.0.9 (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached python_multipart-0.0.9-py3-none-any.whl.metadata (2.5 kB) Collecting ruff>=0.2.2 (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached ruff-0.5.6-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (24 kB) Collecting semantic-version~=2.0 (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached semantic_version-2.10.0-py2.py3-none-any.whl.metadata (9.7 kB) Collecting tomlkit==0.12.0 (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached tomlkit-0.12.0-py3-none-any.whl.metadata (2.7 kB) Requirement already satisfied: typer<1.0,>=0.12 in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (0.12.3) Requirement already satisfied: urllib3~=2.0 in /usr/local/lib/python3.10/dist-packages (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (2.0.7) Collecting uvicorn>=0.14.0 (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached uvicorn-0.30.5-py3-none-any.whl.metadata (6.6 kB) Collecting websockets<12.0,>=10.0 (from gradio-client==1.1.1->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached websockets-11.0.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.6 kB) Requirement already satisfied: setuptools>=18.5 in /usr/local/lib/python3.10/dist-packages (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (71.0.4) Collecting jedi>=0.16 (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) Using cached jedi-0.19.1-py2.py3-none-any.whl.metadata (22 kB) Requirement already satisfied: decorator in /usr/local/lib/python3.10/dist-packages (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (4.4.2) Requirement already satisfied: pickleshare in /usr/local/lib/python3.10/dist-packages (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (0.7.5) Requirement already satisfied: traitlets>=4.2 in /usr/local/lib/python3.10/dist-packages (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (5.7.1) Requirement already satisfied: prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (3.0.47) Requirement already satisfied: pygments in /usr/local/lib/python3.10/dist-packages (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (2.16.1) Requirement already satisfied: backcall in /usr/local/lib/python3.10/dist-packages (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (0.2.0) Requirement already satisfied: matplotlib-inline in /usr/local/lib/python3.10/dist-packages (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (0.1.7) Requirement already satisfied: pexpect>4.3 in /usr/local/lib/python3.10/dist-packages (from ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (4.9.0) Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5.0.0,>=4.23.0->lavague-core<0.3.0,>=0.2.31->lavague) (23.2.0) Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5.0.0,>=4.23.0->lavague-core<0.3.0,>=0.2.31->lavague) (2023.12.1) Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5.0.0,>=4.23.0->lavague-core<0.3.0,>=0.2.31->lavague) (0.35.1) Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5.0.0,>=4.23.0->lavague-core<0.3.0,>=0.2.31->lavague) (0.19.1) Requirement already satisfied: async-timeout<5.0.0,>=4.0.0 in /usr/local/lib/python3.10/dist-packages (from langchain<0.2.0,>=0.1.20->lavague-core<0.3.0,>=0.2.31->lavague) (4.0.3) Collecting langchain-community<0.1,>=0.0.38 (from langchain<0.2.0,>=0.1.20->lavague-core<0.3.0,>=0.2.31->lavague) Using cached langchain_community-0.0.38-py3-none-any.whl.metadata (8.7 kB) Collecting langchain-core<0.2.0,>=0.1.52 (from langchain<0.2.0,>=0.1.20->lavague-core<0.3.0,>=0.2.31->lavague) Using cached langchain_core-0.1.52-py3-none-any.whl.metadata (5.9 kB) Collecting langchain-text-splitters<0.1,>=0.0.1 (from langchain<0.2.0,>=0.1.20->lavague-core<0.3.0,>=0.2.31->lavague) Using cached langchain_text_splitters-0.0.2-py3-none-any.whl.metadata (2.2 kB) Collecting langsmith<0.2.0,>=0.1.17 (from langchain<0.2.0,>=0.1.20->lavague-core<0.3.0,>=0.2.31->lavague) Using cached langsmith-0.1.98-py3-none-any.whl.metadata (13 kB) INFO: pip is looking at multiple versions of llama-index-llms-openai to determine which version is compatible with other requirements. This could take a while. Collecting llama-index-llms-openai<0.2.0,>=0.1.9 (from lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached llama_index_llms_openai-0.1.26-py3-none-any.whl.metadata (610 bytes) Collecting rank-bm25<0.3.0,>=0.2.2 (from llama-index-retrievers-bm25<0.2.0,>=0.1.3->lavague-core<0.3.0,>=0.2.31->lavague) Using cached rank_bm25-0.2.2-py3-none-any.whl.metadata (3.2 kB) Collecting trio~=0.17 (from selenium<5.0.0,>=4.18.1->lavague-drivers-selenium<0.3.0,>=0.2.12->lavague) Using cached trio-0.26.1-py3-none-any.whl.metadata (8.6 kB) Collecting trio-websocket~=0.9 (from selenium<5.0.0,>=4.18.1->lavague-drivers-selenium<0.3.0,>=0.2.12->lavague) Using cached trio_websocket-0.11.1-py3-none-any.whl.metadata (4.7 kB) Requirement already satisfied: certifi>=2021.10.8 in /usr/local/lib/python3.10/dist-packages (from selenium<5.0.0,>=4.18.1->lavague-drivers-selenium<0.3.0,>=0.2.12->lavague) (2024.7.4) Requirement already satisfied: websocket-client~=1.8 in /usr/local/lib/python3.10/dist-packages (from selenium<5.0.0,>=4.18.1->lavague-drivers-selenium<0.3.0,>=0.2.12->lavague) (1.8.0) Collecting courlan>=1.2.0 (from trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) Using cached courlan-1.3.0-py3-none-any.whl.metadata (17 kB) Collecting htmldate>=1.8.1 (from trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) Using cached htmldate-1.8.1-py3-none-any.whl.metadata (10 kB) Collecting justext>=3.0.1 (from trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) Using cached jusText-3.0.1-py2.py3-none-any.whl.metadata (6.9 kB) Requirement already satisfied: charset-normalizer>=3.2.0 in /usr/local/lib/python3.10/dist-packages (from trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) (3.3.2) Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.6->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (2.3.4) Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.6->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.3.1) Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.6->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.4.1) Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.6->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (6.0.5) Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.6->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.9.4) Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.10/dist-packages (from anyio<5.0,>=3.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (3.7) Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<5.0,>=3.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (1.3.1) Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5.0,>=3.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (1.2.2) Collecting azure-core>=1.23.0 (from azure-identity<2.0.0,>=1.15.0->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached azure_core-1.30.2-py3-none-any.whl.metadata (37 kB) Requirement already satisfied: cryptography>=2.5 in /usr/local/lib/python3.10/dist-packages (from azure-identity<2.0.0,>=1.15.0->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (42.0.8) Collecting msal>=1.24.0 (from azure-identity<2.0.0,>=1.15.0->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached msal-1.30.0-py3-none-any.whl.metadata (11 kB) Collecting msal-extensions>=0.3.0 (from azure-identity<2.0.0,>=1.15.0->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached msal_extensions-1.2.0-py3-none-any.whl.metadata (7.6 kB) Requirement already satisfied: babel>=2.15.0 in /usr/local/lib/python3.10/dist-packages (from courlan>=1.2.0->trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) (2.15.0) Collecting tld>=0.13 (from courlan>=1.2.0->trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) Using cached tld-0.13-py2.py3-none-any.whl.metadata (9.4 kB) Collecting marshmallow<4.0.0,>=3.18.0 (from dataclasses-json->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached marshmallow-3.21.3-py3-none-any.whl.metadata (7.1 kB) Collecting dateparser>=1.1.2 (from htmldate>=1.8.1->trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) Using cached dateparser-1.2.0-py2.py3-none-any.whl.metadata (28 kB) Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from htmldate>=1.8.1->trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) (2.8.2) Collecting httpcore==1.* (from httpx->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached httpcore-1.0.5-py3-none-any.whl.metadata (20 kB) Collecting h11<0.15,>=0.13 (from httpcore==1.*->httpx->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached h11-0.14.0-py3-none-any.whl.metadata (8.2 kB) Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.19.3->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (3.15.4) Requirement already satisfied: parso<0.9.0,>=0.8.3 in /usr/local/lib/python3.10/dist-packages (from jedi>=0.16->ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (0.8.4) Collecting jsonpatch<2.0,>=1.33 (from langchain-core<0.2.0,>=0.1.52->langchain<0.2.0,>=0.1.20->lavague-core<0.3.0,>=0.2.31->lavague) Using cached jsonpatch-1.33-py2.py3-none-any.whl.metadata (3.0 kB) Collecting packaging (from gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached packaging-23.2-py3-none-any.whl.metadata (3.2 kB) Collecting llama-cloud>=0.0.11 (from llama-index-indices-managed-llama-cloud>=0.2.0->llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_cloud-0.0.11-py3-none-any.whl.metadata (751 bytes) INFO: pip is looking at multiple versions of llama-index-program-openai to determine which version is compatible with other requirements. This could take a while. Collecting llama-index-program-openai<0.2.0,>=0.1.3 (from llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_index_program_openai-0.1.6-py3-none-any.whl.metadata (715 bytes) Requirement already satisfied: beautifulsoup4<5.0.0,>=4.12.3 in /usr/local/lib/python3.10/dist-packages (from llama-index-readers-file<0.2.0,>=0.1.4->llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) (4.12.3) Collecting pypdf<5.0.0,>=4.0.1 (from llama-index-readers-file<0.2.0,>=0.1.4->llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached pypdf-4.3.1-py3-none-any.whl.metadata (7.4 kB) Collecting striprtf<0.0.27,>=0.0.26 (from llama-index-readers-file<0.2.0,>=0.1.4->llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached striprtf-0.0.26-py3-none-any.whl.metadata (2.1 kB) Collecting llama-parse>=0.4.0 (from llama-index-readers-llama-parse>=0.1.2->llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) Using cached llama_parse-0.4.9-py3-none-any.whl.metadata (4.4 kB) Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib~=3.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (1.2.1) Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib~=3.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (0.12.1) Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib~=3.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (4.53.1) Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib~=3.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (1.4.5) Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib~=3.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (3.1.2) Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (2024.1) Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (2024.1) Requirement already satisfied: ptyprocess>=0.5 in /usr/local/lib/python3.10/dist-packages (from pexpect>4.3->ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (0.7.0) Requirement already satisfied: wcwidth in /usr/local/lib/python3.10/dist-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython<8.0.0,>=7.34.0->lavague-core<0.3.0,>=0.2.31->lavague) (0.2.13) Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic>=2.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (0.7.0) Requirement already satisfied: pydantic-core==2.20.1 in /usr/local/lib/python3.10/dist-packages (from pydantic>=2.0->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (2.20.1) Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy>=1.4.49->SQLAlchemy[asyncio]>=1.4.49->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (3.0.3) Requirement already satisfied: sortedcontainers in /usr/local/lib/python3.10/dist-packages (from trio~=0.17->selenium<5.0.0,>=4.18.1->lavague-drivers-selenium<0.3.0,>=0.2.12->lavague) (2.4.0) Collecting outcome (from trio~=0.17->selenium<5.0.0,>=4.18.1->lavague-drivers-selenium<0.3.0,>=0.2.12->lavague) Using cached outcome-1.3.0.post0-py2.py3-none-any.whl.metadata (2.6 kB) Collecting wsproto>=0.14 (from trio-websocket~=0.9->selenium<5.0.0,>=4.18.1->lavague-drivers-selenium<0.3.0,>=0.2.12->lavague) Using cached wsproto-1.2.0-py3-none-any.whl.metadata (5.6 kB) Requirement already satisfied: click>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from typer<1.0,>=0.12->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (8.1.7) Requirement already satisfied: shellingham>=1.3.0 in /usr/local/lib/python3.10/dist-packages (from typer<1.0,>=0.12->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (1.5.4) Requirement already satisfied: rich>=10.11.0 in /usr/local/lib/python3.10/dist-packages (from typer<1.0,>=0.12->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (13.7.1) Requirement already satisfied: pysocks!=1.5.7,<2.0,>=1.5.6 in /usr/local/lib/python3.10/dist-packages (from urllib3[socks]<3,>=1.26->selenium<5.0.0,>=4.18.1->lavague-drivers-selenium<0.3.0,>=0.2.12->lavague) (1.7.1) Collecting starlette<0.38.0,>=0.37.2 (from fastapi->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) Using cached starlette-0.37.2-py3-none-any.whl.metadata (5.9 kB) Requirement already satisfied: six>=1.11.0 in /usr/local/lib/python3.10/dist-packages (from azure-core>=1.23.0->azure-identity<2.0.0,>=1.15.0->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.16.0) Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4<5.0.0,>=4.12.3->llama-index-readers-file<0.2.0,>=0.1.4->llama-index==0.10.56->lavague-core<0.3.0,>=0.2.31->lavague) (2.5) Requirement already satisfied: cffi>=1.12 in /usr/local/lib/python3.10/dist-packages (from cryptography>=2.5->azure-identity<2.0.0,>=1.15.0->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.16.0) Requirement already satisfied: regex!=2019.02.19,!=2021.8.27 in /usr/local/lib/python3.10/dist-packages (from dateparser>=1.1.2->htmldate>=1.8.1->trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) (2024.5.15) Requirement already satisfied: tzlocal in /usr/local/lib/python3.10/dist-packages (from dateparser>=1.1.2->htmldate>=1.8.1->trafilatura<2.0.0,>=1.9.0->lavague-core<0.3.0,>=0.2.31->lavague) (5.2) Collecting jsonpointer>=1.9 (from jsonpatch<2.0,>=1.33->langchain-core<0.2.0,>=0.1.52->langchain<0.2.0,>=0.1.20->lavague-core<0.3.0,>=0.2.31->lavague) Using cached jsonpointer-3.0.0-py2.py3-none-any.whl.metadata (2.3 kB) Requirement already satisfied: PyJWT<3,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from PyJWT[crypto]<3,>=1.0.0->msal>=1.24.0->azure-identity<2.0.0,>=1.15.0->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (2.9.0) Collecting portalocker<3,>=1.4 (from msal-extensions>=0.3.0->azure-identity<2.0.0,>=1.15.0->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached portalocker-2.10.1-py3-none-any.whl.metadata (8.5 kB) Requirement already satisfied: joblib in /usr/local/lib/python3.10/dist-packages (from nltk<4.0.0,>=3.8.1->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.4.2) Requirement already satisfied: distro<2,>=1.7.0 in /usr/lib/python3/dist-packages (from openai>=1.1.0->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (1.7.0) Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich>=10.11.0->typer<1.0,>=0.12->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (3.0.0) Collecting mypy-extensions>=0.3.0 (from typing-inspect>=0.8.0->llama-index-core<0.11.0,>=0.10.11.post1->llama-index-embeddings-azure-openai==0.1.11->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) Using cached mypy_extensions-1.0.0-py3-none-any.whl.metadata (1.1 kB) Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.12->cryptography>=2.5->azure-identity<2.0.0,>=1.15.0->llama-index-llms-azure-openai==0.1.10->lavague-contexts-openai<0.3.0,>=0.2.0->lavague) (2.22) Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich>=10.11.0->typer<1.0,>=0.12->gradio==4.39.0->lavague-gradio<0.3.0,>=0.2.8->lavague) (0.1.2) Using cached lavague-1.1.19-py3-none-any.whl (8.4 kB) Using cached lavague_contexts_openai-0.2.4-py3-none-any.whl (2.5 kB) Using cached llama_index_embeddings_azure_openai-0.1.11-py3-none-any.whl (3.3 kB) Using cached llama_index_llms_azure_openai-0.1.10-py3-none-any.whl (5.1 kB) Using cached llama_index_multi_modal_llms_azure_openai-0.1.4-py3-none-any.whl (3.7 kB) Using cached lavague_core-0.2.32-py3-none-any.whl (53 kB) Using cached llama_index-0.10.56-py3-none-any.whl (6.8 kB) Downloading llama_index_core-0.10.56-py3-none-any.whl (15.5 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 15.5/15.5 MB 41.8 MB/s eta 0:00:00 Downloading lavague_drivers_selenium-0.2.12-py3-none-any.whl (9.1 kB) Downloading lavague_gradio-0.2.8-py3-none-any.whl (3.5 kB) Downloading gradio-4.39.0-py3-none-any.whl (12.4 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.4/12.4 MB 57.3 MB/s eta 0:00:00 Downloading gradio_client-1.1.1-py3-none-any.whl (318 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 318.2/318.2 kB 16.1 MB/s eta 0:00:00 Downloading tomlkit-0.12.0-py3-none-any.whl (37 kB) Downloading langchain-0.1.20-py3-none-any.whl (1.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.0/1.0 MB 31.6 MB/s eta 0:00:00 Downloading llama_index_embeddings_openai-0.1.11-py3-none-any.whl (6.3 kB) Downloading llama_index_llms_openai-0.1.26-py3-none-any.whl (11 kB) Downloading llama_index_multi_modal_llms_openai-0.1.8-py3-none-any.whl (5.9 kB) Downloading llama_index_retrievers_bm25-0.1.5-py3-none-any.whl (2.8 kB) Downloading lxml-5.2.2-cp310-cp310-manylinux_2_28_x86_64.whl (5.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 5.0/5.0 MB 61.2 MB/s eta 0:00:00 Downloading lxml_html_clean-0.1.1-py3-none-any.whl (11 kB) Downloading seaborn-0.13.2-py3-none-any.whl (294 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 294.9/294.9 kB 17.6 MB/s eta 0:00:00 Downloading selenium-4.23.1-py3-none-any.whl (9.4 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.4/9.4 MB 73.1 MB/s eta 0:00:00 Downloading tenacity-8.3.0-py3-none-any.whl (25 kB) Downloading trafilatura-1.12.0-py3-none-any.whl (130 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 131.0/131.0 kB 8.0 MB/s eta 0:00:00 Downloading aiofiles-23.2.1-py3-none-any.whl (15 kB) Downloading azure_identity-1.17.1-py3-none-any.whl (173 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 173.2/173.2 kB 11.2 MB/s eta 0:00:00 Downloading courlan-1.3.0-py3-none-any.whl (33 kB) Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) Downloading htmldate-1.8.1-py3-none-any.whl (31 kB) Downloading httpx-0.27.0-py3-none-any.whl (75 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 75.6/75.6 kB 4.8 MB/s eta 0:00:00 Downloading httpcore-1.0.5-py3-none-any.whl (77 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 77.9/77.9 kB 5.5 MB/s eta 0:00:00 Using cached jedi-0.19.1-py2.py3-none-any.whl (1.6 MB) Downloading jusText-3.0.1-py2.py3-none-any.whl (837 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 837.8/837.8 kB 39.8 MB/s eta 0:00:00 Downloading langchain_community-0.0.38-py3-none-any.whl (2.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.0/2.0 MB 46.5 MB/s eta 0:00:00 Downloading langchain_core-0.1.52-py3-none-any.whl (302 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 302.9/302.9 kB 18.9 MB/s eta 0:00:00 Downloading langchain_text_splitters-0.0.2-py3-none-any.whl (23 kB) Downloading langsmith-0.1.98-py3-none-any.whl (140 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 140.2/140.2 kB 8.5 MB/s eta 0:00:00 Downloading llama_index_agent_openai-0.2.9-py3-none-any.whl (13 kB) Downloading llama_index_cli-0.1.13-py3-none-any.whl (27 kB) Downloading llama_index_indices_managed_llama_cloud-0.2.7-py3-none-any.whl (9.5 kB) Downloading llama_index_legacy-0.9.48-py3-none-any.whl (2.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.0/2.0 MB 55.6 MB/s eta 0:00:00 Downloading llama_index_program_openai-0.1.6-py3-none-any.whl (5.2 kB) Downloading llama_index_question_gen_openai-0.1.3-py3-none-any.whl (2.9 kB) Downloading llama_index_readers_file-0.1.32-py3-none-any.whl (38 kB) Downloading llama_index_readers_llama_parse-0.1.6-py3-none-any.whl (2.5 kB) Downloading orjson-3.10.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (141 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 141.1/141.1 kB 8.9 MB/s eta 0:00:00 Downloading packaging-23.2-py3-none-any.whl (53 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 53.0/53.0 kB 3.2 MB/s eta 0:00:00 Downloading python_multipart-0.0.9-py3-none-any.whl (22 kB) Downloading rank_bm25-0.2.2-py3-none-any.whl (8.6 kB) Downloading ruff-0.5.6-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 10.2/10.2 MB 81.3 MB/s eta 0:00:00 Downloading semantic_version-2.10.0-py2.py3-none-any.whl (15 kB) Downloading trio-0.26.1-py3-none-any.whl (475 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 475.7/475.7 kB 26.5 MB/s eta 0:00:00 Downloading trio_websocket-0.11.1-py3-none-any.whl (17 kB) Downloading uvicorn-0.30.5-py3-none-any.whl (62 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 62.8/62.8 kB 3.6 MB/s eta 0:00:00 Downloading fastapi-0.112.0-py3-none-any.whl (93 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 93.1/93.1 kB 5.5 MB/s eta 0:00:00 Downloading ffmpy-0.4.0-py3-none-any.whl (5.8 kB) Downloading pydub-0.25.1-py2.py3-none-any.whl (32 kB) Downloading azure_core-1.30.2-py3-none-any.whl (194 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 194.3/194.3 kB 12.2 MB/s eta 0:00:00 Downloading dateparser-1.2.0-py2.py3-none-any.whl (294 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 295.0/295.0 kB 17.9 MB/s eta 0:00:00 Downloading Deprecated-1.2.14-py2.py3-none-any.whl (9.6 kB) Downloading dirtyjson-1.0.8-py3-none-any.whl (25 kB) Downloading h11-0.14.0-py3-none-any.whl (58 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 58.3/58.3 kB 3.3 MB/s eta 0:00:00 Downloading jsonpatch-1.33-py2.py3-none-any.whl (12 kB) Downloading llama_cloud-0.0.11-py3-none-any.whl (154 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 154.8/154.8 kB 10.2 MB/s eta 0:00:00 Downloading llama_parse-0.4.9-py3-none-any.whl (9.4 kB) Downloading marshmallow-3.21.3-py3-none-any.whl (49 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 49.2/49.2 kB 3.0 MB/s eta 0:00:00 Downloading msal-1.30.0-py3-none-any.whl (111 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 111.8/111.8 kB 7.6 MB/s eta 0:00:00 Downloading msal_extensions-1.2.0-py3-none-any.whl (19 kB) Downloading openai-1.39.0-py3-none-any.whl (336 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 336.7/336.7 kB 20.5 MB/s eta 0:00:00 Downloading pypdf-4.3.1-py3-none-any.whl (295 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 295.8/295.8 kB 16.6 MB/s eta 0:00:00 Downloading starlette-0.37.2-py3-none-any.whl (71 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 71.9/71.9 kB 4.7 MB/s eta 0:00:00 Downloading striprtf-0.0.26-py3-none-any.whl (6.9 kB) Downloading tiktoken-0.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 42.9 MB/s eta 0:00:00 Downloading tld-0.13-py2.py3-none-any.whl (263 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 263.8/263.8 kB 16.5 MB/s eta 0:00:00 Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) Downloading websockets-11.0.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (129 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 129.9/129.9 kB 8.5 MB/s eta 0:00:00 Downloading wsproto-1.2.0-py3-none-any.whl (24 kB) Downloading outcome-1.3.0.post0-py2.py3-none-any.whl (10 kB) Downloading jsonpointer-3.0.0-py2.py3-none-any.whl (7.6 kB) Downloading mypy_extensions-1.0.0-py3-none-any.whl (4.7 kB) Downloading portalocker-2.10.1-py3-none-any.whl (18 kB) Installing collected packages: striprtf, pydub, dirtyjson, websockets, tomlkit, tld, tenacity, semantic-version, ruff, rank-bm25, python-multipart, pypdf, portalocker, packaging, outcome, orjson, mypy-extensions, lxml, jsonpointer, jedi, h11, ffmpy, deprecated, aiofiles, wsproto, uvicorn, typing-inspect, trio, tiktoken, starlette, marshmallow, lxml-html-clean, jsonpatch, httpcore, dateparser, courlan, azure-core, trio-websocket, seaborn, langsmith, httpx, htmldate, fastapi, dataclasses-json, selenium, openai, msal, llama-cloud, langchain-core, justext, gradio-client, trafilatura, msal-extensions, llama-index-legacy, llama-index-core, langchain-text-splitters, langchain-community, gradio, llama-parse, llama-index-retrievers-bm25, llama-index-readers-file, llama-index-llms-openai, llama-index-indices-managed-llama-cloud, llama-index-embeddings-openai, langchain, azure-identity, llama-index-readers-llama-parse, llama-index-multi-modal-llms-openai, llama-index-llms-azure-openai, llama-index-cli, llama-index-agent-openai, llama-index-program-openai, llama-index-multi-modal-llms-azure-openai, llama-index-embeddings-azure-openai, llama-index-question-gen-openai, llama-index, lavague-core, lavague-gradio, lavague-drivers-selenium, lavague-contexts-openai, lavague Attempting uninstall: tomlkit Found existing installation: tomlkit 0.13.0 Uninstalling tomlkit-0.13.0: Successfully uninstalled tomlkit-0.13.0 Attempting uninstall: tenacity Found existing installation: tenacity 9.0.0 Uninstalling tenacity-9.0.0: Successfully uninstalled tenacity-9.0.0 Attempting uninstall: packaging Found existing installation: packaging 24.1 Uninstalling packaging-24.1: Successfully uninstalled packaging-24.1 Attempting uninstall: lxml Found existing installation: lxml 4.9.4 Uninstalling lxml-4.9.4: Successfully uninstalled lxml-4.9.4 Attempting uninstall: seaborn Found existing installation: seaborn 0.13.1 Uninstalling seaborn-0.13.1: Successfully uninstalled seaborn-0.13.1 Successfully installed aiofiles-23.2.1 azure-core-1.30.2 azure-identity-1.17.1 courlan-1.3.0 dataclasses-json-0.6.7 dateparser-1.2.0 deprecated-1.2.14 dirtyjson-1.0.8 fastapi-0.112.0 ffmpy-0.4.0 gradio-4.39.0 gradio-client-1.1.1 h11-0.14.0 htmldate-1.8.1 httpcore-1.0.5 httpx-0.27.0 jedi-0.19.1 jsonpatch-1.33 jsonpointer-3.0.0 justext-3.0.1 langchain-0.1.20 langchain-community-0.0.38 langchain-core-0.1.52 langchain-text-splitters-0.0.2 langsmith-0.1.98 lavague-1.1.19 lavague-contexts-openai-0.2.4 lavague-core-0.2.32 lavague-drivers-selenium-0.2.12 lavague-gradio-0.2.8 llama-cloud-0.0.11 llama-index-0.10.56 llama-index-agent-openai-0.2.9 llama-index-cli-0.1.13 llama-index-core-0.10.56 llama-index-embeddings-azure-openai-0.1.11 llama-index-embeddings-openai-0.1.11 llama-index-indices-managed-llama-cloud-0.2.7 llama-index-legacy-0.9.48 llama-index-llms-azure-openai-0.1.10 llama-index-llms-openai-0.1.26 llama-index-multi-modal-llms-azure-openai-0.1.4 llama-index-multi-modal-llms-openai-0.1.8 llama-index-program-openai-0.1.6 llama-index-question-gen-openai-0.1.3 llama-index-readers-file-0.1.32 llama-index-readers-llama-parse-0.1.6 llama-index-retrievers-bm25-0.1.5 llama-parse-0.4.9 lxml-5.2.2 lxml-html-clean-0.1.1 marshmallow-3.21.3 msal-1.30.0 msal-extensions-1.2.0 mypy-extensions-1.0.0 openai-1.39.0 orjson-3.10.6 outcome-1.3.0.post0 packaging-23.2 portalocker-2.10.1 pydub-0.25.1 pypdf-4.3.1 python-multipart-0.0.9 rank-bm25-0.2.2 ruff-0.5.6 seaborn-0.13.2 selenium-4.23.1 semantic-version-2.10.0 starlette-0.37.2 striprtf-0.0.26 tenacity-8.3.0 tiktoken-0.7.0 tld-0.13 tomlkit-0.12.0 trafilatura-1.12.0 trio-0.26.1 trio-websocket-0.11.1 typing-inspect-0.9.0 uvicorn-0.30.5 websockets-11.0.3 wsproto-1.2.0
Instantiate a Word Model¶
In [4]:
Copied!
from lavague.core import WorldModel
world_model = WorldModel()
from lavague.core import WorldModel
world_model = WorldModel()
[nltk_data] Downloading package stopwords to
[nltk_data] /usr/local/lib/python3.10/dist-
[nltk_data] packages/llama_index/legacy/_static/nltk_cache...
[nltk_data] Unzipping corpora/stopwords.zip.
[nltk_data] Downloading package punkt to
[nltk_data] /usr/local/lib/python3.10/dist-
[nltk_data] packages/llama_index/legacy/_static/nltk_cache...
[nltk_data] Unzipping tokenizers/punkt.zip.
/usr/local/lib/python3.10/dist-packages/lavague/core/__init__.py:21: UserWarning: Telemetry is turned on. To turn off telemetry, set your LAVAGUE_TELEMETRY to 'NONE'
warnings.warn(warning_message, UserWarning)
Generate observations¶
In [5]:
Copied!
from lavague.drivers.selenium import SeleniumDriver
from lavague.core.memory import ShortTermMemory
selenium_driver = SeleniumDriver(headless=True, url="https://huggingface.co/")
st_memory = ShortTermMemory()
# Generate observations & set objective
objective = "Go on the quicktour of PEFT"
current_state, past = st_memory.get_state()
obs = selenium_driver.get_obs()
from lavague.drivers.selenium import SeleniumDriver
from lavague.core.memory import ShortTermMemory
selenium_driver = SeleniumDriver(headless=True, url="https://huggingface.co/")
st_memory = ShortTermMemory()
# Generate observations & set objective
objective = "Go on the quicktour of PEFT"
current_state, past = st_memory.get_state()
obs = selenium_driver.get_obs()
In [6]:
Copied!
from lavague.core.logger import load_images_from_folder
from IPython.display import display
images = load_images_from_folder(obs["screenshots_path"])
display(images[0])
from lavague.core.logger import load_images_from_folder
from IPython.display import display
images = load_images_from_folder(obs["screenshots_path"])
display(images[0])
In [7]:
Copied!
print("Objective: ", objective)
print("Current State: ", current_state)
print("Past: ", past)
print("Observations: ", obs)
print("Objective: ", objective)
print("Current State: ", current_state)
print("Past: ", past)
print("Observations: ", obs)
Objective: Go on the quicktour of PEFT
Current State: {'external_observations': {'vision': '[SCREENSHOT]'}, 'internal_state': {'user_inputs': [], 'agent_outputs': []}}
Past: {'previous_instructions': '[NONE]', 'last_engine': '[NONE]'}
Observations: {'html': '<html class=""><head>\n\t\t<meta charset="utf-8">\n\t\t<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=no">\n\t\t<meta name="description" content="We’re on a journey to advance and democratize artificial intelligence through open source and open science.">\n\t\t<meta property="fb:app_id" content="1321688464574422">\n\t\t<meta name="twitter:card" content="summary_large_image">\n\t\t<meta name="twitter:site" content="@huggingface">\n\t\t<meta property="og:title" content="Hugging Face – The AI community building the future.">\n\t\t<meta property="og:type" content="website">\n\t\t<meta property="og:url" content="https://huggingface.co/">\n\t\t<meta property="og:image" content="https://huggingface.co/front/thumbnails/v2-2.png">\n\n\t\t<link rel="stylesheet" href="/front/build/kube-8a64282/style.css">\n\n\t\t<link rel="preconnect" href="https://fonts.gstatic.com">\n\t\t<link href="https://fonts.googleapis.com/css2?family=Source+Sans+Pro:ital,wght@0,200;0,300;0,400;0,600;0,700;0,900;1,200;1,300;1,400;1,600;1,700;1,900&display=swap" rel="stylesheet">\n\t\t<link href="https://fonts.googleapis.com/css2?family=IBM+Plex+Mono:wght@400;600;700&display=swap" rel="stylesheet">\n\n\t\t<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.12.0/katex.min.css" as="style" onload="this.onload=null;this.rel=\'stylesheet\'">\n\t\t<noscript>\n\t\t\t<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.12.0/katex.min.css" />\n\t\t</noscript>\n\n\t\t<link rel="canonical" href="https://huggingface.co/"> <!-- HEAD_svelte-vwinwk_START --><link rel="alternate" type="application/rss+xml" href="/blog/feed.xml" title="Hugging Face Blog"><!-- HEAD_svelte-vwinwk_END -->\n\n\t\t<title>Hugging Face – The AI community building the future.</title>\n\n\t\t<script defer="" data-domain="huggingface.co" event-loggedin="false" src="/js/script.pageview-props.js"></script>\n\t\t<script>\n\t\t\twindow.plausible =\n\t\t\t\twindow.plausible ||\n\t\t\t\tfunction () {\n\t\t\t\t\t(window.plausible.q = window.plausible.q || []).push(arguments);\n\t\t\t\t};\n\t\t</script>\n\t\t<script>\n\t\t\twindow.hubConfig = JSON.parse(`{"features":{"signupDisabled":false},"sshGitUrl":"git@hf.co","moonHttpUrl":"https://huggingface.co","captchaApiKey":"bd5f2066-93dc-4bdd-a64b-a24646ca3859","captchaDisabledOnSignup":true,"datasetViewerPublicUrl":"https://datasets-server.huggingface.co","stripePublicKey":"pk_live_x2tdjFXBCvXo2FFmMybezpeM00J6gPCAAc","environment":"production","userAgent":"HuggingFace (production)","spacesIframeDomain":"hf.space","spacesApiUrl":"https://api.hf.space","docSearchKey":"ece5e02e57300e17d152c08056145326e90c4bff3dd07d7d1ae40cf1c8d39cb6","logoDev":{"apiUrl":"https://img.logo.dev/","apiKey":"pk_UHS2HZOeRnaSOdDp7jbd5w"}}`);\n\t\t</script>\n\t\t<script type="text/javascript" src="https://de5282c3ca0c.edge.sdk.awswaf.com/de5282c3ca0c/526cf06acb0d/challenge.js" defer=""></script>\n\t<script src="https://js.stripe.com/v3/" async=""></script></head>\n\t<body class="flex flex-col min-h-screen bg-white dark:bg-gray-950 text-black HomePage">\n\t\t\n\n<div class="flex min-h-screen flex-col">\n\t<div class="SVELTE_HYDRATER contents" data-target="MainHeader" data-props="{"classNames":"!border-transparent","isWide":false,"isZh":true}"><header class="border-b border-gray-100 !border-transparent"><div class="w-full px-4 container flex h-16 items-center"><div class="flex flex-1 items-center"><a class="mr-5 flex flex-none items-center lg:mr-6" href="/"><img alt="Hugging Face\'s logo" class="w-7 md:mr-2" src="/front/assets/huggingface_logo-noborder.svg"> <span class="hidden whitespace-nowrap text-lg font-bold md:block">Hugging Face</span></a> <div class="relative flex-1 lg:max-w-sm mr-2 sm:mr-4 md:mr-3 xl:mr-6"><input autocomplete="off" class="w-full dark:bg-gray-950 pl-8 form-input-alt h-9 pr-3 focus:shadow-xl " name="" placeholder="Search models, datasets, users..." spellcheck="false" type="text"> <svg class="absolute left-2.5 text-gray-400 top-1/2 transform -translate-y-1/2" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M30 28.59L22.45 21A11 11 0 1 0 21 22.45L28.59 30zM5 14a9 9 0 1 1 9 9a9 9 0 0 1-9-9z" fill="currentColor"></path></svg> </div> <div class="flex flex-none items-center justify-center p-0.5 place-self-stretch lg:hidden"><button class="relative z-40 flex h-6 w-8 items-center justify-center" type="button"><svg width="1em" height="1em" viewBox="0 0 10 10" class="text-xl" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" preserveAspectRatio="xMidYMid meet" fill="currentColor"><path fill-rule="evenodd" clip-rule="evenodd" d="M1.65039 2.9999C1.65039 2.8066 1.80709 2.6499 2.00039 2.6499H8.00039C8.19369 2.6499 8.35039 2.8066 8.35039 2.9999C8.35039 3.1932 8.19369 3.3499 8.00039 3.3499H2.00039C1.80709 3.3499 1.65039 3.1932 1.65039 2.9999ZM1.65039 4.9999C1.65039 4.8066 1.80709 4.6499 2.00039 4.6499H8.00039C8.19369 4.6499 8.35039 4.8066 8.35039 4.9999C8.35039 5.1932 8.19369 5.3499 8.00039 5.3499H2.00039C1.80709 5.3499 1.65039 5.1932 1.65039 4.9999ZM2.00039 6.6499C1.80709 6.6499 1.65039 6.8066 1.65039 6.9999C1.65039 7.1932 1.80709 7.3499 2.00039 7.3499H8.00039C8.19369 7.3499 8.35039 7.1932 8.35039 6.9999C8.35039 6.8066 8.19369 6.6499 8.00039 6.6499H2.00039Z"></path></svg> </button> </div></div> <nav aria-label="Main" class="ml-auto hidden lg:block"><ul class="flex items-center space-x-1.5 xl:space-x-2"><li><a class="group flex items-center px-2 py-0.5 dark:hover:text-gray-400 hover:text-indigo-700" href="/models"><svg class="mr-1.5 text-gray-400 group-hover:text-indigo-500" style="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-quaternary" d="M20.23 7.24L12 12L3.77 7.24a1.98 1.98 0 0 1 .7-.71L11 2.76c.62-.35 1.38-.35 2 0l6.53 3.77c.29.173.531.418.7.71z" opacity=".25" fill="currentColor"></path><path class="uim-tertiary" d="M12 12v9.5a2.09 2.09 0 0 1-.91-.21L4.5 17.48a2.003 2.003 0 0 1-1-1.73v-7.5a2.06 2.06 0 0 1 .27-1.01L12 12z" opacity=".5" fill="currentColor"></path><path class="uim-primary" d="M20.5 8.25v7.5a2.003 2.003 0 0 1-1 1.73l-6.62 3.82c-.275.13-.576.198-.88.2V12l8.23-4.76c.175.308.268.656.27 1.01z" fill="currentColor"></path></svg> Models</a></li><li><a class="group flex items-center px-2 py-0.5 dark:hover:text-gray-400 hover:text-red-700" href="/datasets"><svg class="mr-1.5 text-gray-400 group-hover:text-red-500" style="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 25 25"><ellipse cx="12.5" cy="5" fill="currentColor" fill-opacity="0.25" rx="7.5" ry="2"></ellipse><path d="M12.5 15C16.6421 15 20 14.1046 20 13V20C20 21.1046 16.6421 22 12.5 22C8.35786 22 5 21.1046 5 20V13C5 14.1046 8.35786 15 12.5 15Z" fill="currentColor" opacity="0.5"></path><path d="M12.5 7C16.6421 7 20 6.10457 20 5V11.5C20 12.6046 16.6421 13.5 12.5 13.5C8.35786 13.5 5 12.6046 5 11.5V5C5 6.10457 8.35786 7 12.5 7Z" fill="currentColor" opacity="0.5"></path><path d="M5.23628 12C5.08204 12.1598 5 12.8273 5 13C5 14.1046 8.35786 15 12.5 15C16.6421 15 20 14.1046 20 13C20 12.8273 19.918 12.1598 19.7637 12C18.9311 12.8626 15.9947 13.5 12.5 13.5C9.0053 13.5 6.06886 12.8626 5.23628 12Z" fill="currentColor"></path></svg> Datasets</a></li><li><a class="group flex items-center px-2 py-0.5 dark:hover:text-gray-400 hover:text-blue-700" href="/spaces"><svg class="mr-1.5 text-gray-400 group-hover:text-blue-500" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 25 25"><path opacity=".5" d="M6.016 14.674v4.31h4.31v-4.31h-4.31ZM14.674 14.674v4.31h4.31v-4.31h-4.31ZM6.016 6.016v4.31h4.31v-4.31h-4.31Z" fill="currentColor"></path><path opacity=".75" fill-rule="evenodd" clip-rule="evenodd" d="M3 4.914C3 3.857 3.857 3 4.914 3h6.514c.884 0 1.628.6 1.848 1.414a5.171 5.171 0 0 1 7.31 7.31c.815.22 1.414.964 1.414 1.848v6.514A1.914 1.914 0 0 1 20.086 22H4.914A1.914 1.914 0 0 1 3 20.086V4.914Zm3.016 1.102v4.31h4.31v-4.31h-4.31Zm0 12.968v-4.31h4.31v4.31h-4.31Zm8.658 0v-4.31h4.31v4.31h-4.31Zm0-10.813a2.155 2.155 0 1 1 4.31 0 2.155 2.155 0 0 1-4.31 0Z" fill="currentColor"></path><path opacity=".25" d="M16.829 6.016a2.155 2.155 0 1 0 0 4.31 2.155 2.155 0 0 0 0-4.31Z" fill="currentColor"></path></svg> Spaces</a></li><li><a class="group flex items-center px-2 py-0.5 dark:hover:text-gray-400 hover:text-yellow-700" href="/posts"><svg class="mr-1.5 text-gray-400 group-hover:text-yellow-500 !text-yellow-500" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 12 12" preserveAspectRatio="xMidYMid meet"><path fill="currentColor" fill-rule="evenodd" d="M3.73 2.4A4.25 4.25 0 1 1 6 10.26H2.17l-.13-.02a.43.43 0 0 1-.3-.43l.01-.06a.43.43 0 0 1 .12-.22l.84-.84A4.26 4.26 0 0 1 3.73 2.4Z" clip-rule="evenodd"></path></svg> Posts</a></li><li><a class="group flex items-center px-2 py-0.5 dark:hover:text-gray-400 hover:text-yellow-700" href="/docs"><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="mr-1.5 text-gray-400 group-hover:text-yellow-500" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path opacity="0.5" d="M20.9022 5.10334L10.8012 10.8791L7.76318 9.11193C8.07741 8.56791 8.5256 8.11332 9.06512 7.7914L15.9336 3.73907C17.0868 3.08811 18.5002 3.26422 19.6534 3.91519L19.3859 3.73911C19.9253 4.06087 20.5879 4.56025 20.9022 5.10334Z" fill="currentColor"></path><path d="M10.7999 10.8792V28.5483C10.2136 28.5475 9.63494 28.4139 9.10745 28.1578C8.5429 27.8312 8.074 27.3621 7.74761 26.7975C7.42122 26.2327 7.24878 25.5923 7.24756 24.9402V10.9908C7.25062 10.3319 7.42358 9.68487 7.74973 9.1123L10.7999 10.8792Z" fill="currentColor" fill-opacity="0.75"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M21.3368 10.8499V6.918C21.3331 6.25959 21.16 5.61234 20.8346 5.03949L10.7971 10.8727L10.8046 10.874L21.3368 10.8499Z" fill="currentColor"></path><path opacity="0.5" d="M21.7937 10.8488L10.7825 10.8741V28.5486L21.7937 28.5234C23.3344 28.5234 24.5835 27.2743 24.5835 25.7335V13.6387C24.5835 12.0979 23.4365 11.1233 21.7937 10.8488Z" fill="currentColor"></path></svg> Docs</a></li> <li class="max-2xl:hidden"><div class="relative "><button class="px-2 py-0.5 group hover:text-green-700 dark:hover:text-gray-400 flex items-center " type="button"><svg class="mr-1.5 text-gray-400 group-hover:text-green-500" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-tertiary" d="M19 6H5a3 3 0 0 0-3 3v2.72L8.837 14h6.326L22 11.72V9a3 3 0 0 0-3-3z" opacity=".5" fill="currentColor"></path><path class="uim-primary" d="M10 6V5h4v1h2V5a2.002 2.002 0 0 0-2-2h-4a2.002 2.002 0 0 0-2 2v1h2zm-1.163 8L2 11.72V18a3.003 3.003 0 0 0 3 3h14a3.003 3.003 0 0 0 3-3v-6.28L15.163 14H8.837z" fill="currentColor"></path></svg> Solutions </button> </div></li> <li><a class="group flex items-center px-2 py-0.5 hover:text-gray-500 dark:hover:text-gray-400" href="/pricing">Pricing</a></li> <li><div class="relative group"><button class="px-2 py-0.5 hover:text-gray-500 dark:hover:text-gray-600 flex items-center " type="button"><svg class=" text-gray-500 w-5 group-hover:text-gray-400 dark:text-gray-300 dark:group-hover:text-gray-400" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 32 18" preserveAspectRatio="xMidYMid meet"><path fill-rule="evenodd" clip-rule="evenodd" d="M14.4504 3.30221C14.4504 2.836 14.8284 2.45807 15.2946 2.45807H28.4933C28.9595 2.45807 29.3374 2.836 29.3374 3.30221C29.3374 3.76842 28.9595 4.14635 28.4933 4.14635H15.2946C14.8284 4.14635 14.4504 3.76842 14.4504 3.30221Z" fill="currentColor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.4504 9.00002C14.4504 8.53382 14.8284 8.15588 15.2946 8.15588H28.4933C28.9595 8.15588 29.3374 8.53382 29.3374 9.00002C29.3374 9.46623 28.9595 9.84417 28.4933 9.84417H15.2946C14.8284 9.84417 14.4504 9.46623 14.4504 9.00002Z" fill="currentColor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M14.4504 14.6978C14.4504 14.2316 14.8284 13.8537 15.2946 13.8537H28.4933C28.9595 13.8537 29.3374 14.2316 29.3374 14.6978C29.3374 15.164 28.9595 15.542 28.4933 15.542H15.2946C14.8284 15.542 14.4504 15.164 14.4504 14.6978Z" fill="currentColor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M1.94549 6.87377C2.27514 6.54411 2.80962 6.54411 3.13928 6.87377L6.23458 9.96907L9.32988 6.87377C9.65954 6.54411 10.194 6.54411 10.5237 6.87377C10.8533 7.20343 10.8533 7.73791 10.5237 8.06756L6.23458 12.3567L1.94549 8.06756C1.61583 7.73791 1.61583 7.20343 1.94549 6.87377Z" fill="currentColor"></path></svg> </button> </div></li> <li><hr class="h-5 w-0.5 border-none bg-gray-100 dark:bg-gray-800"></li> <li><a class="block cursor-pointer px-2 py-0.5 hover:text-gray-500 dark:hover:text-gray-400" href="/login">Log In</a></li> <li><a class="rounded-full border border-transparent bg-gray-900 px-3 py-1 leading-none text-white hover:border-black hover:bg-white hover:text-black" href="/join">Sign Up</a></li></ul></nav></div></header></div>\n\t\n\t\n\t\n\t<div class="SVELTE_HYDRATER contents" data-target="SSOBanner" data-props="{}"></div>\n\t\n\n\t<main class="flex flex-1 flex-col"><div class="container pt-2 md:pt-14 2xl:pt-20"><div class="relative flex flex-col justify-center rounded-[25px] bg-gray-950 max-lg:items-center max-lg:overflow-hidden max-lg:pt-20 max-lg:text-center lg:h-[620px] lg:p-16 xl:p-24 2xl:h-[720px]"><a href="/chat" class="group absolute top-4 flex h-7 w-fit items-center whitespace-nowrap rounded-lg bg-gray-500/30 px-2 text-smd leading-none text-white hover:bg-gray-500/40 max-lg:mx-auto md:top-6 lg:left-6"><div class="mr-2 self-center rounded bg-gradient-to-r from-indigo-500 to-purple-500 px-1 text-xs font-semibold text-white/80">NEW\n\t\t\t\t</div>\n\t\t\t\t<div class="underline decoration-gray-500 group-hover:decoration-gray-300">AI Tools are now available in HuggingChat\n\t\t\t\t</div></a>\n\t\t\t<img src="/front/assets/huggingface_logo-noborder.svg" class="-mt-3 mb-7 w-20" alt="">\n\n\t\t\t<h1 class="relative mb-6 max-w-lg text-4xl font-bold text-white lg:mb-10 lg:text-5xl 2xl:max-w-xl 2xl:text-6xl" style="text-wrap:balance;">The AI community building the future.\n\t\t\t</h1>\n\t\t\t<p class="max-w-lg text-gray-300/80 max-lg:mb-16 max-lg:px-6 lg:pr-6 lg:text-lg" style="text-wrap: balance;">The platform where the machine learning community collaborates on models, datasets, and applications.\n\t\t\t</p>\n\t\t\t<div class="grainy absolute right-2/3 h-[250px] w-[250px] translate-x-1/2 translate-y-16 rounded-full md:h-[600px] md:w-[600px] md:translate-y-2 lg:right-1/2 lg:translate-y-6"></div>\n\t\t\t<img src="/front/assets/homepage/models-mobile.svg" alt="Hugging Face models" class="pointer-events-none relative mb-0 select-none lg:hidden">\n\t\t\t<img src="/front/assets/homepage/models-tablet.svg" alt="Hugging Face models" class="pointer-events-none absolute bottom-0 right-0 hidden h-[650px] select-none lg:block xl:hidden 2xl:h-[760px]">\n\t\t\t<img src="/front/assets/homepage/models.svg" alt="Hugging Face models" class="pointer-events-none absolute bottom-0 right-0 h-[650px] select-none max-xl:hidden 2xl:h-[760px]">\n\t\t\t<div class="absolute inset-x-0 -bottom-4 z-10 h-5 w-full rounded-[50%] bg-white lg:h-6"></div></div></div>\n\n\t<div class="container mx-auto mb-16 pt-12 sm:mb-32 sm:pt-20"><div class="mb-10 flex items-center justify-center gap-2 text-xl font-bold sm:mb-14"><div class="mr-2 h-px flex-1 translate-y-px bg-gradient-to-l from-gray-200 to-white"></div>\n\t\t\tTrending on<img src="/front/assets/huggingface_logo-noborder.svg" class="w-8" alt="">this week\n\t\t\t<div class="ml-2 h-px flex-1 translate-y-px bg-gradient-to-r from-gray-200 to-white"></div></div>\n\t\t<div class="relative grid grid-cols-1 gap-6 lg:grid-cols-3"><div class="absolute h-full w-2/3 bg-gradient-to-br from-indigo-200/30 to-red-100/40 blur-2xl max-lg:translate-x-1/3 lg:h-96 lg:w-full lg:translate-y-24 lg:-rotate-2 lg:rounded-[50%] lg:from-indigo-200/80 lg:via-red-100/60 lg:to-gray-50"></div>\n\t\t\t<div class="relative col-span-1 flex flex-col items-stretch text-center"><h2 class="mb-5 flex items-center justify-center gap-2 text-lg font-semibold 2xl:mb-6 2xl:text-xl"><svg class="text-gray-500" style="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-quaternary" d="M20.23 7.24L12 12L3.77 7.24a1.98 1.98 0 0 1 .7-.71L11 2.76c.62-.35 1.38-.35 2 0l6.53 3.77c.29.173.531.418.7.71z" opacity=".25" fill="currentColor"></path><path class="uim-tertiary" d="M12 12v9.5a2.09 2.09 0 0 1-.91-.21L4.5 17.48a2.003 2.003 0 0 1-1-1.73v-7.5a2.06 2.06 0 0 1 .27-1.01L12 12z" opacity=".5" fill="currentColor"></path><path class="uim-primary" d="M20.5 8.25v7.5a2.003 2.003 0 0 1-1 1.73l-6.62 3.82c-.275.13-.576.198-.88.2V12l8.23-4.76c.175.308.268.656.27 1.01z" fill="currentColor"></path></svg>\n\t\t\t\t\tModels\n\t\t\t\t</h2>\n\t\t\t\t<div class="mb-3 flex flex-col gap-2.5 rounded-xl bg-white/40 p-3 backdrop-blur-lg sm:mb-7"><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/black-forest-labs/FLUX.1-dev"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="black-forest-labs/FLUX.1-dev">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-indigo-600 text-smd">black-forest-labs/FLUX.1-dev</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2024-08-05T21:37:24" title="Mon, 05 Aug 2024 21:37:24 GMT">about 11 hours ago</time></span>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t1.09k\n\n\t\t\t\t</div></div>\n\t\t</a></article><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/black-forest-labs/FLUX.1-schnell"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="black-forest-labs/FLUX.1-schnell">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-indigo-600 text-smd">black-forest-labs/FLUX.1-schnell</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2024-08-05T21:37:34" title="Mon, 05 Aug 2024 21:37:34 GMT">about 11 hours ago</time></span>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t843\n\n\t\t\t\t</div></div>\n\t\t</a></article><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/meta-llama/Meta-Llama-3.1-8B-Instruct"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="meta-llama/Meta-Llama-3.1-8B-Instruct">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-indigo-600 text-smd">meta-llama/Meta-Llama-3.1-8B-Instruct</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2024-07-30T12:46:01" title="Tue, 30 Jul 2024 12:46:01 GMT">7 days ago</time></span>\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-0.5" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 32 32"><path fill="currentColor" d="M26 24v4H6v-4H4v4a2 2 0 0 0 2 2h20a2 2 0 0 0 2-2v-4zm0-10l-1.41-1.41L17 20.17V2h-2v18.17l-7.59-7.58L6 14l10 10l10-10z"></path></svg>\n\t\t\t\t\t677k\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t1.51k\n\n\t\t\t\t</div></div>\n\t\t</a></article><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/google/gemma-2-2b-it"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="google/gemma-2-2b-it">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-indigo-600 text-smd">google/gemma-2-2b-it</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2024-07-31T10:07:47" title="Wed, 31 Jul 2024 10:07:47 GMT">6 days ago</time></span>\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-0.5" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 32 32"><path fill="currentColor" d="M26 24v4H6v-4H4v4a2 2 0 0 0 2 2h20a2 2 0 0 0 2-2v-4zm0-10l-1.41-1.41L17 20.17V2h-2v18.17l-7.59-7.58L6 14l10 10l10-10z"></path></svg>\n\t\t\t\t\t29.6k\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t329\n\n\t\t\t\t</div></div>\n\t\t</a></article><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/Kijai/flux-fp8"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="Kijai/flux-fp8">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-indigo-600 text-smd">Kijai/flux-fp8</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2024-08-03T10:20:37" title="Sat, 03 Aug 2024 10:20:37 GMT">3 days ago</time></span>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t225\n\n\t\t\t\t</div></div>\n\t\t</a></article></div>\n\t\t\t\t<a href="/models" class="self-center underline decoration-gray-300 underline-offset-8 transition-all hover:decoration-gray-800 hover:underline-offset-[6px] max-sm:mb-5">Browse 400k+ models</a></div>\n\t\t\t<div class="relative col-span-1 flex flex-col items-stretch text-center"><h2 class="mb-5 flex items-center justify-center gap-2 text-lg font-semibold 2xl:mb-6 2xl:text-xl"><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M7.80914 18.7462V24.1907H13.2536V18.7462H7.80914Z" fill="#FF3270"></path><path d="M18.7458 18.7462V24.1907H24.1903V18.7462H18.7458Z" fill="#861FFF"></path><path d="M7.80914 7.80982V13.2543H13.2536V7.80982H7.80914Z" fill="#097EFF"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M4 6.41775C4 5.08246 5.08246 4 6.41775 4H14.6457C15.7626 4 16.7026 4.75724 16.9802 5.78629C18.1505 4.67902 19.7302 4 21.4685 4C25.0758 4 28.0003 6.92436 28.0003 10.5317C28.0003 12.27 27.3212 13.8497 26.2139 15.02C27.243 15.2977 28.0003 16.2376 28.0003 17.3545V25.5824C28.0003 26.9177 26.9177 28.0003 25.5824 28.0003H17.0635H14.9367H6.41775C5.08246 28.0003 4 26.9177 4 25.5824V15.1587V14.9367V6.41775ZM7.80952 7.80952V13.254H13.254V7.80952H7.80952ZM7.80952 24.1907V18.7462H13.254V24.1907H7.80952ZM18.7462 24.1907V18.7462H24.1907V24.1907H18.7462ZM18.7462 10.5317C18.7462 9.0283 19.9651 7.80952 21.4685 7.80952C22.9719 7.80952 24.1907 9.0283 24.1907 10.5317C24.1907 12.0352 22.9719 13.254 21.4685 13.254C19.9651 13.254 18.7462 12.0352 18.7462 10.5317Z" fill="black"></path><path d="M21.4681 7.80982C19.9647 7.80982 18.7458 9.02861 18.7458 10.5321C18.7458 12.0355 19.9647 13.2543 21.4681 13.2543C22.9715 13.2543 24.1903 12.0355 24.1903 10.5321C24.1903 9.02861 22.9715 7.80982 21.4681 7.80982Z" fill="#FFD702"></path></svg>\n\t\t\t\t\tSpaces\n\t\t\t\t</h2>\n\t\t\t\t<div class="mb-3 flex flex-col gap-2.5 rounded-xl bg-white/40 p-3 backdrop-blur-lg sm:mb-7"><article class="">\n\t<a href="/spaces/black-forest-labs/FLUX.1-schnell" class="relative z-0 mx-auto flex flex-col items-center justify-center bg-gradient-to-br p-4 filter from-yellow-600 to-pink-600 overflow-hidden hover:brightness-110 h-16 rounded-lg"><div class="absolute left-0 top-0 h-24 w-1/2 bg-gradient-to-br from-black/20 via-transparent to-transparent"></div>\n\t\t<div class="absolute right-16 flex flex-wrap content-start gap-1 overflow-hidden hidden">\n\t\t\t<div class="inline-flex cursor-pointer select-none items-center overflow-hidden font-mono inline-flex items-center rounded border !border-white/5 bg-white/10 leading-tight text-white opacity-80"><div class="inline-flex items-center px-1 py-0">\n\t\tRunning\n\t\t\n\t\t\t<span class="mx-1">on </span>\n\t\t\t<span class="-skew-x-6 truncate font-bold uppercase">Zero</span></div>\n\t</div>\n\n\t\t\t\n\n\t\t\t</div>\n\n\t\t<div class="absolute flex items-center rounded-xl top-2 right-3.5 text-xs"><svg class="mr-1.5 text-white" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t<span class="text-white">804</span></div>\n\t\t<div class="absolute opacity-60 text-4xl drop-shadow">🏎️💨</div>\n\t\t<h4 class="z-40 max-w-full truncate text-center font-bold leading-tight text-blue-50 text-md " style="text-shadow: 0px 1px 2px rgba(0, 0, 0, 0.25);">FLUX.1 [Schnell]</h4>\n\t\t</a>\n\t</article><article class="">\n\t<a href="/spaces/black-forest-labs/FLUX.1-dev" class="relative z-0 mx-auto flex flex-col items-center justify-center bg-gradient-to-br p-4 filter from-yellow-600 to-pink-600 overflow-hidden hover:brightness-110 h-16 rounded-lg"><div class="absolute left-0 top-0 h-24 w-1/2 bg-gradient-to-br from-black/20 via-transparent to-transparent"></div>\n\t\t<div class="absolute right-16 flex flex-wrap content-start gap-1 overflow-hidden hidden">\n\t\t\t<div class="inline-flex cursor-pointer select-none items-center overflow-hidden font-mono inline-flex items-center rounded border !border-white/5 bg-white/10 leading-tight text-white opacity-80"><div class="inline-flex items-center px-1 py-0">\n\t\tRunning\n\t\t\n\t\t\t<span class="mx-1">on </span>\n\t\t\t<span class="-skew-x-6 truncate font-bold uppercase">Zero</span></div>\n\t</div>\n\n\t\t\t\n\n\t\t\t</div>\n\n\t\t<div class="absolute flex items-center rounded-xl top-2 right-3.5 text-xs"><svg class="mr-1.5 text-white" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t<span class="text-white">490</span></div>\n\t\t<div class="absolute opacity-60 text-4xl drop-shadow">🖥️</div>\n\t\t<h4 class="z-40 max-w-full truncate text-center font-bold leading-tight text-blue-50 text-md " style="text-shadow: 0px 1px 2px rgba(0, 0, 0, 0.25);">FLUX.1 [dev]</h4>\n\t\t</a>\n\t</article><article class="">\n\t<a href="/spaces/stabilityai/stable-fast-3d" class="relative z-0 mx-auto flex flex-col items-center justify-center bg-gradient-to-br p-4 filter from-purple-600 to-indigo-600 overflow-hidden hover:brightness-110 h-16 rounded-lg"><div class="absolute left-0 top-0 h-24 w-1/2 bg-gradient-to-br from-black/20 via-transparent to-transparent"></div>\n\t\t<div class="absolute right-16 flex flex-wrap content-start gap-1 overflow-hidden hidden">\n\t\t\t<div class="inline-flex cursor-pointer select-none items-center overflow-hidden font-mono inline-flex items-center rounded border !border-white/5 bg-white/10 leading-tight text-white opacity-80"><div class="inline-flex items-center px-1 py-0">\n\t\tRunning\n\t\t\n\t\t\t<span class="mx-1">on </span>\n\t\t\t<span class="-skew-x-6 truncate font-bold uppercase">L4</span></div>\n\t</div>\n\n\t\t\t\n\n\t\t\t</div>\n\n\t\t<div class="absolute flex items-center rounded-xl top-2 right-3.5 text-xs"><svg class="mr-1.5 text-white" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t<span class="text-white">251</span></div>\n\t\t<div class="absolute opacity-60 text-4xl drop-shadow">🎮</div>\n\t\t<h4 class="z-40 max-w-full truncate text-center font-bold leading-tight text-blue-50 text-md " style="text-shadow: 0px 1px 2px rgba(0, 0, 0, 0.25);">Stable Fast 3D</h4>\n\t\t</a>\n\t</article><article class="">\n\t<a href="/spaces/KwaiVGI/LivePortrait" class="relative z-0 mx-auto flex flex-col items-center justify-center bg-gradient-to-br p-4 filter from-red-600 to-yellow-600 overflow-hidden hover:brightness-110 h-16 rounded-lg"><div class="absolute left-0 top-0 h-24 w-1/2 bg-gradient-to-br from-black/20 via-transparent to-transparent"></div>\n\t\t<div class="absolute right-16 flex flex-wrap content-start gap-1 overflow-hidden hidden">\n\t\t\t<div class="inline-flex cursor-pointer select-none items-center overflow-hidden font-mono inline-flex items-center rounded border !border-white/5 bg-white/10 leading-tight text-white opacity-80"><div class="inline-flex items-center px-1 py-0">\n\t\tRunning\n\t\t\n\t\t\t<span class="mx-1">on </span>\n\t\t\t<span class="-skew-x-6 truncate font-bold uppercase">Zero</span></div>\n\t</div>\n\n\t\t\t\n\n\t\t\t</div>\n\n\t\t<div class="absolute flex items-center rounded-xl top-2 right-3.5 text-xs"><svg class="mr-1.5 text-white" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t<span class="text-white">1.52k</span></div>\n\t\t<div class="absolute opacity-60 text-4xl drop-shadow">🤪</div>\n\t\t<h4 class="z-40 max-w-full truncate text-center font-bold leading-tight text-blue-50 text-md " style="text-shadow: 0px 1px 2px rgba(0, 0, 0, 0.25);">Live Portrait</h4>\n\t\t<div class="hidden absolute bottom-0 right-0 z-40 flex max-w-[93%] items-center"><svg xmlns="http://www.w3.org/2000/svg" preserveAspectRatio="xMidYMid meet" class="pointer-events-none absolute left-0 h-full -translate-x-full text-black/15" viewBox="0 0 16 12"><path fill="currentColor" d="M9.49 6.13C8.07 10.7 6.09 12 0 12h16V0c-3.5 0-4.97 1.2-6.51 6.13Z"></path></svg>\n\n\t\t\t\t<p class="truncate break-words bg-black/15 py-0.5 pr-2 text-[0.78rem] leading-tight text-white/75">Apply the motion of a video on a portrait</p></div></a>\n\t</article><article class="">\n\t<a href="/spaces/llamameta/llama3.1-405B" class="relative z-0 mx-auto flex flex-col items-center justify-center bg-gradient-to-br p-4 filter from-red-600 to-purple-600 overflow-hidden hover:brightness-110 h-16 rounded-lg"><div class="absolute left-0 top-0 h-24 w-1/2 bg-gradient-to-br from-black/20 via-transparent to-transparent"></div>\n\t\t<div class="absolute right-16 flex flex-wrap content-start gap-1 overflow-hidden hidden">\n\t\t\t<div class="inline-flex cursor-pointer select-none items-center overflow-hidden font-mono inline-flex items-center rounded border !border-white/5 bg-white/10 leading-tight text-white opacity-80"><div class="inline-flex items-center px-1 py-0">\n\t\tRunning\n\t\t</div>\n\t</div>\n\n\t\t\t\n\n\t\t\t</div>\n\n\t\t<div class="absolute flex items-center rounded-xl top-2 right-3.5 text-xs"><svg class="mr-1.5 text-white" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t<span class="text-white">427</span></div>\n\t\t<div class="absolute opacity-60 text-4xl drop-shadow">🌖</div>\n\t\t<h4 class="z-40 max-w-full truncate text-center font-bold leading-tight text-blue-50 text-md " style="text-shadow: 0px 1px 2px rgba(0, 0, 0, 0.25);">Llama3.1 405B</h4>\n\t\t</a>\n\t</article></div>\n\t\t\t\t<a href="/spaces" class="self-center underline decoration-gray-300 underline-offset-8 transition-all hover:decoration-gray-800 hover:underline-offset-[6px] max-sm:mb-5">Browse 150k+ applications</a></div>\n\t\t\t<div class="relative col-span-1 flex flex-col items-stretch text-center"><h2 class="mb-5 flex items-center justify-center gap-2 text-lg font-semibold 2xl:mb-6 2xl:text-xl"><svg class="text-gray-500" style="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 25 25"><ellipse cx="12.5" cy="5" fill="currentColor" fill-opacity="0.25" rx="7.5" ry="2"></ellipse><path d="M12.5 15C16.6421 15 20 14.1046 20 13V20C20 21.1046 16.6421 22 12.5 22C8.35786 22 5 21.1046 5 20V13C5 14.1046 8.35786 15 12.5 15Z" fill="currentColor" opacity="0.5"></path><path d="M12.5 7C16.6421 7 20 6.10457 20 5V11.5C20 12.6046 16.6421 13.5 12.5 13.5C8.35786 13.5 5 12.6046 5 11.5V5C5 6.10457 8.35786 7 12.5 7Z" fill="currentColor" opacity="0.5"></path><path d="M5.23628 12C5.08204 12.1598 5 12.8273 5 13C5 14.1046 8.35786 15 12.5 15C16.6421 15 20 14.1046 20 13C20 12.8273 19.918 12.1598 19.7637 12C18.9311 12.8626 15.9947 13.5 12.5 13.5C9.0053 13.5 6.06886 12.8626 5.23628 12Z" fill="currentColor"></path></svg>\n\t\t\t\t\tDatasets\n\t\t\t\t</h2>\n\t\t\t\t<div class="mb-3 flex flex-col gap-2.5 rounded-xl bg-white/40 p-3 backdrop-blur-lg sm:mb-7"><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/datasets/argilla/magpie-ultra-v0.1"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="argilla/magpie-ultra-v0.1">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-red-600 text-smd">argilla/magpie-ultra-v0.1</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2024-08-05T08:26:17" title="Mon, 05 Aug 2024 08:26:17 GMT">1 day ago</time></span>\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-0.5" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 32 32"><path fill="currentColor" d="M26 24v4H6v-4H4v4a2 2 0 0 0 2 2h20a2 2 0 0 0 2-2v-4zm0-10l-1.41-1.41L17 20.17V2h-2v18.17l-7.59-7.58L6 14l10 10l10-10z"></path></svg>\n\t\t\t\t\t87\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t116\n\n\t\t\t\t</div></div>\n\t\t</a></article><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/datasets/fka/awesome-chatgpt-prompts"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="fka/awesome-chatgpt-prompts">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-red-600 text-smd">fka/awesome-chatgpt-prompts</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2023-03-07T10:04:18" title="Tue, 07 Mar 2023 10:04:18 GMT">Mar 7, 2023</time></span>\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-0.5" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 32 32"><path fill="currentColor" d="M26 24v4H6v-4H4v4a2 2 0 0 0 2 2h20a2 2 0 0 0 2-2v-4zm0-10l-1.41-1.41L17 20.17V2h-2v18.17l-7.59-7.58L6 14l10 10l10-10z"></path></svg>\n\t\t\t\t\t6.87k\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t5.13k\n\n\t\t\t\t</div></div>\n\t\t</a></article><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/datasets/Vezora/Open-Critic-GPT"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="Vezora/Open-Critic-GPT">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-red-600 text-smd">Vezora/Open-Critic-GPT</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2024-07-28T21:00:25" title="Sun, 28 Jul 2024 21:00:25 GMT">8 days ago</time></span>\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-0.5" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 32 32"><path fill="currentColor" d="M26 24v4H6v-4H4v4a2 2 0 0 0 2 2h20a2 2 0 0 0 2-2v-4zm0-10l-1.41-1.41L17 20.17V2h-2v18.17l-7.59-7.58L6 14l10 10l10-10z"></path></svg>\n\t\t\t\t\t248\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t41\n\n\t\t\t\t</div></div>\n\t\t</a></article><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/datasets/AI-MO/NuminaMath-CoT"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="AI-MO/NuminaMath-CoT">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-red-600 text-smd">AI-MO/NuminaMath-CoT</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2024-07-19T13:58:59" title="Fri, 19 Jul 2024 13:58:59 GMT">18 days ago</time></span>\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-0.5" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 32 32"><path fill="currentColor" d="M26 24v4H6v-4H4v4a2 2 0 0 0 2 2h20a2 2 0 0 0 2-2v-4zm0-10l-1.41-1.41L17 20.17V2h-2v18.17l-7.59-7.58L6 14l10 10l10-10z"></path></svg>\n\t\t\t\t\t4.4k\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t144\n\n\t\t\t\t</div></div>\n\t\t</a></article><article class="overview-card-wrapper group/repo white "><a class="flex items-center justify-between gap-4 p-2" href="/datasets/mlabonne/FineTome-100k"><div class="w-full truncate"><header class="flex items-center mb-0.5" title="mlabonne/FineTome-100k">\n\t\t\t\t<h4 class="text-md truncate font-mono text-black dark:group-hover/repo:text-yellow-500 group-hover/repo:text-red-600 text-smd">mlabonne/FineTome-100k</h4>\n\t\t\t\t</header>\n\t\t\t<div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400">\n\t\t\t\t<span class="truncate">Updated\n\t\t\t\t\t<time datetime="2024-07-29T09:52:30" title="Mon, 29 Jul 2024 09:52:30 GMT">8 days ago</time></span>\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-0.5" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 32 32"><path fill="currentColor" d="M26 24v4H6v-4H4v4a2 2 0 0 0 2 2h20a2 2 0 0 0 2-2v-4zm0-10l-1.41-1.41L17 20.17V2h-2v18.17l-7.59-7.58L6 14l10 10l10-10z"></path></svg>\n\t\t\t\t\t3.33k\n\t\t\t\t\n\t\t\t\t<span class="px-1.5 text-gray-300 dark:text-gray-500">• </span>\n\t\t\t\t\t<svg class="flex-none w-3 text-gray-400 mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" fill="currentColor"><path d="M22.45,6a5.47,5.47,0,0,1,3.91,1.64,5.7,5.7,0,0,1,0,8L16,26.13,5.64,15.64a5.7,5.7,0,0,1,0-8,5.48,5.48,0,0,1,7.82,0L16,10.24l2.53-2.58A5.44,5.44,0,0,1,22.45,6m0-2a7.47,7.47,0,0,0-5.34,2.24L16,7.36,14.89,6.24a7.49,7.49,0,0,0-10.68,0,7.72,7.72,0,0,0,0,10.82L16,29,27.79,17.06a7.72,7.72,0,0,0,0-10.82A7.49,7.49,0,0,0,22.45,4Z"></path></svg>\n\t\t\t\t\t32\n\n\t\t\t\t</div></div>\n\t\t</a></article></div>\n\t\t\t\t<a href="/datasets" class="self-center underline decoration-gray-300 underline-offset-8 transition-all hover:decoration-gray-800 hover:underline-offset-[6px] max-sm:mb-5">Browse 100k+ datasets</a></div></div></div>\n\n\t<div class="container"><div class="mb-28 flex h-48 w-full flex-col items-stretch rounded-t-[50%] bg-gradient-to-b from-gray-100/60 via-white to-white pt-24 text-center 2xl:mb-32"><svg class="text-3xl 2xl:text-4xl self-center text-gray-900 mb-2 sm:mb-4 flex-none" style="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-quaternary" d="M20.23 7.24L12 12L3.77 7.24a1.98 1.98 0 0 1 .7-.71L11 2.76c.62-.35 1.38-.35 2 0l6.53 3.77c.29.173.531.418.7.71z" opacity=".25" fill="currentColor"></path><path class="uim-tertiary" d="M12 12v9.5a2.09 2.09 0 0 1-.91-.21L4.5 17.48a2.003 2.003 0 0 1-1-1.73v-7.5a2.06 2.06 0 0 1 .27-1.01L12 12z" opacity=".5" fill="currentColor"></path><path class="uim-primary" d="M20.5 8.25v7.5a2.003 2.003 0 0 1-1 1.73l-6.62 3.82c-.275.13-.576.198-.88.2V12l8.23-4.76c.175.308.268.656.27 1.01z" fill="currentColor"></path></svg>\n\n\t\t\t<div class="mb-2 flex flex-none items-center justify-center gap-2 text-xl font-bold"><div class="mr-4 h-px flex-1 bg-gradient-to-l from-gray-100 to-white"></div>\n\t\t\t\t<h2 class="text-3xl font-bold 2xl:text-4xl" style="text-wrap: balance;">The Home of Machine Learning</h2>\n\t\t\t\t<div class="ml-4 h-px flex-1 bg-gradient-to-r from-gray-100 to-white"></div></div>\n\n\t\t\t<p class="flex-none text-lg text-gray-500 2xl:text-xl" style="text-wrap: balance;">Create, discover and collaborate on ML better.\n\t\t\t</p></div>\n\n\t\t<div class="mx-auto grid max-w-5xl gap-4 md:gap-8 lg:grid-cols-3 2xl:max-w-7xl"><div class="relative col-span-1 flex h-[400px] flex-col overflow-hidden rounded-xl border bg-white shadow-sm sm:h-[420px] lg:col-span-2 2xl:h-[500px]"><div class="p-6 md:p-8"><h3 class="text-xl font-semibold 2xl:text-2xl">The collaboration platform</h3>\n\t\t\t\t\t<p class="text-base text-gray-500 2xl:text-lg">Host and collaborate on unlimited models, datasets and applications.\n\t\t\t\t\t</p></div>\n\t\t\t\t<img src="/front/assets/homepage/activity.svg" class="ml-auto w-full flex-1 overflow-hidden border-t border-gray-100 object-cover object-left-top" alt="Hub activity feed">\n\t\t\t\t<div class="pointer-events-none absolute inset-x-0 bottom-0 h-40 select-none bg-gradient-to-tl from-white/80 to-white/0"></div></div>\n\t\t\t<div class="relative col-span-1 flex h-[390px] flex-col overflow-hidden rounded-xl border bg-white shadow-sm sm:h-[420px] 2xl:h-[500px]"><div class="p-6 md:p-8"><h3 class="text-xl font-semibold 2xl:text-2xl">Move faster</h3>\n\t\t\t\t\t<p class="text-base text-gray-500 2xl:text-lg">With the HF Open source stack.</p></div>\n\t\t\t\t<img src="/front/assets/homepage/snippets.svg" class="ml-auto w-full flex-1 overflow-hidden border-t border-gray-100 object-cover object-left-top" alt="Code snippets from HF libraries">\n\t\t\t\t<div class="pointer-events-none absolute inset-x-0 bottom-0 h-40 select-none bg-gradient-to-tl from-white/80 to-white/0"></div></div>\n\t\t\t<div class="relative col-span-1 flex h-[390px] flex-col overflow-hidden rounded-xl border bg-white shadow-sm sm:h-[420px] 2xl:h-[500px]"><div class="p-6 md:p-8"><h3 class="text-xl font-semibold 2xl:text-2xl">Explore all modalities</h3>\n\t\t\t\t\t<p class="text-base text-gray-500 2xl:text-lg">Text, image, video, audio or even 3D.</p></div>\n\t\t\t\t<img src="/front/assets/homepage/modalities.svg" class="ml-auto w-full overflow-hidden border-t border-gray-100 bg-gray-50 object-cover" alt="Hugging face tasks "></div>\n\t\t\t<div class="relative col-span-1 flex h-[390px] flex-col overflow-hidden rounded-xl border bg-white shadow-sm sm:h-[420px] lg:col-span-2 2xl:h-[500px]"><div class="flex justify-between p-6 md:p-8"><div><h3 class="text-xl font-semibold 2xl:text-2xl">Build your portfolio</h3>\n\t\t\t\t\t\t<p class="text-base text-gray-500 2xl:text-lg">Share your work with the world and build your ML profile.</p></div>\n\t\t\t\t\t<a class="flex-none self-start rounded-full border border-transparent bg-gray-900 px-2.5 py-1.5 text-smd leading-none text-white hover:border-black hover:bg-white hover:text-black" href="/join">Sign Up\n\t\t\t\t\t</a></div>\n\t\t\t\t<img src="/front/assets/homepage/younes.svg" class="ml-auto w-full flex-1 overflow-hidden border-t border-gray-100 object-cover object-left-top" alt="Younes Belkada Hugging Face profile">\n\t\t\t\t<div class="pointer-events-none absolute inset-x-0 bottom-0 h-40 select-none bg-gradient-to-tl from-white/80 to-white/0"></div></div></div>\n\n\t\t<div class="flex w-full flex-col items-stretch pb-24 pt-24 text-center"><div class="mb-2 flex items-center justify-center gap-2 text-xl font-bold"><div class="mr-4 h-px flex-1 bg-gradient-to-l from-gray-100 to-white"></div>\n\t\t\t\t<h2 class="text-3xl font-bold 2xl:text-4xl">Accelerate your ML</h2>\n\t\t\t\t<div class="ml-4 h-px flex-1 bg-gradient-to-r from-gray-100 to-white"></div></div>\n\n\t\t\t<p class="text-lg text-gray-500 2xl:text-xl" style="text-wrap: balance;">We provide paid Compute and Enterprise solutions.\n\t\t\t</p></div>\n\t\t<div class="mx-auto grid max-w-5xl grid-cols-1 gap-10 2xl:max-w-7xl"><div class="col-span-1 grid h-[450px] grid-cols-1 items-center overflow-hidden rounded-xl border bg-white shadow-sm lg:h-[400px] lg:grid-cols-3"><div class="col-span-1 p-7 md:p-10"><h3 class="mb-4 text-2xl font-semibold">Compute</h3>\n\t\t\t\t\t<p class="mb-6 text-base text-gray-500 lg:mb-8 2xl:text-lg" style="text-wrap: balance;">Deploy on optimized <a class="underline" href="/pricing#endpoints">Inference Endpoints</a> or update your\n\t\t\t\t\t\t<a class="underline" href="/pricing#spaces">Spaces applications</a> to a GPU in a few clicks.\n\t\t\t\t\t</p>\n\t\t\t\t\t<div class="flex items-center gap-x-2.5 whitespace-nowrap sm:gap-x-3.5"><a class="leading-black rounded-lg border border-transparent bg-black px-3.5 py-1 text-base text-white hover:border-black hover:bg-white hover:text-gray-900 2xl:text-lg" href="/pricing">View pricing\n\t\t\t\t\t\t</a>\n\t\t\t\t\t\t<p class="text-smd text-gray-400 2xl:text-base">Starting at $0.60/hour for GPU</p></div></div>\n\t\t\t\t<div class="col-span-1 self-stretch lg:col-span-2"><img src="/front/assets/homepage/compute.svg" alt="Hugging face compute offering" class="pointer-events-none h-full w-full select-none bg-bottom object-cover object-left"></div></div>\n\t\t\t<div class="relative col-span-1 grid h-[450px] grid-cols-1 items-center rounded-xl bg-gradient-to-b from-gray-900 to-gray-950 text-gray-200 shadow-sm lg:h-[400px] lg:grid-cols-3"><div class="col-span-1 p-7 md:p-10"><h3 class="mb-4 text-2xl font-semibold">Enterprise</h3>\n\t\t<p class="mb-6 text-base text-gray-500 lg:mb-8 2xl:text-lg" style="text-wrap: balance;">Give your team the most advanced platform to build AI with enterprise-grade security, access controls and\n\t\t\tdedicated support.\n\t\t</p>\n\t\t<div class="flex items-center gap-x-2.5 whitespace-nowrap sm:gap-x-3.5"><a class="leading-black rounded-lg border border-transparent bg-gray-200 px-3.5 py-1 text-base text-gray-900 hover:border-white hover:bg-black hover:text-white 2xl:text-lg" href="/enterprise">Getting started\n\t\t\t</a>\n\t\t\t<p class="text-smd text-gray-400 2xl:text-base">Starting at $20/user/month</p></div></div>\n\t<div class="col-span-1 self-stretch rounded-r-xl lg:relative lg:col-span-2 lg:ml-8"><div class="absolute right-20 top-8 hidden h-[300px] w-full max-w-2xl lg:block"><a href="/enterprise" class="top-16 left-24 absolute z-2 rounded-lg border border-white/10 bg-white/10 px-4 py-2 text-sm font-semibold text-white backdrop-blur-sm transition-all duration-200 hover:bg-white/15">Single Sign-On</a><a href="/enterprise" class="left-1/2 -translate-x-1/2 absolute z-2 rounded-lg border border-white/10 bg-white/10 px-4 py-2 text-sm font-semibold text-white backdrop-blur-sm transition-all duration-200 hover:bg-white/15">Regions</a><a href="/enterprise" class="right-10 bottom-16 absolute z-2 rounded-lg border border-white/10 bg-white/10 px-4 py-2 text-sm font-semibold text-white backdrop-blur-sm transition-all duration-200 hover:bg-white/15">Priority Support</a><a href="/enterprise" class="left-10 xl:left-6 bottom-1/3 absolute z-2 rounded-lg border border-white/10 bg-white/10 px-4 py-2 text-sm font-semibold text-white backdrop-blur-sm transition-all duration-200 hover:bg-white/15">Audit Logs</a><a href="/enterprise" class="bottom-0 right-1/2 absolute z-2 rounded-lg border border-white/10 bg-white/10 px-4 py-2 text-sm font-semibold text-white backdrop-blur-sm transition-all duration-200 hover:bg-white/15">Ressource Groups</a><a href="/enterprise" class="right-0 top-20 absolute z-2 rounded-lg border border-white/10 bg-white/10 px-4 py-2 text-sm font-semibold text-white backdrop-blur-sm transition-all duration-200 hover:bg-white/15">Private Datasets Viewer</a></div>\n\t\t<div class="pointer-events-none absolute right-0 top-0 hidden h-64 w-64 overflow-hidden rounded-r-xl lg:block"><div class="-translate-y-20 translate-x-16"><svg class="w-full h-full animate__bounce pointer-events-none [animation-duration:11s]" style="--rotation-angle: -30deg;" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-quaternary fill-[#4A4E57]" d="M20.23 7.24L12 12L3.77 7.24a1.98 1.98 0 0 1 .7-.71L11 2.76c.62-.35 1.38-.35 2 0l6.53 3.77c.29.173.531.418.7.71z"></path><path class="uim-tertiary fill-[#86898F]" d="M12 12v9.5a2.09 2.09 0 0 1-.91-.21L4.5 17.48a2.003 2.003 0 0 1-1-1.73v-7.5a2.06 2.06 0 0 1 .27-1.01L12 12z"></path><path class="uim-primary fill-white" d="M20.5 8.25v7.5a2.003 2.003 0 0 1-1 1.73l-6.62 3.82c-.275.13-.576.198-.88.2V12l8.23-4.76c.175.308.268.656.27 1.01z"></path></svg></div></div>\n\t\t<svg class="absolute text-8xl z-1 -top-8 right-32 lg:left-32 animate__bounce pointer-events-none [animation-duration:12s]" style="--rotation-angle: 16deg;" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-quaternary fill-[#4A4E57]" d="M20.23 7.24L12 12L3.77 7.24a1.98 1.98 0 0 1 .7-.71L11 2.76c.62-.35 1.38-.35 2 0l6.53 3.77c.29.173.531.418.7.71z"></path><path class="uim-tertiary fill-[#86898F]" d="M12 12v9.5a2.09 2.09 0 0 1-.91-.21L4.5 17.48a2.003 2.003 0 0 1-1-1.73v-7.5a2.06 2.06 0 0 1 .27-1.01L12 12z"></path><path class="uim-primary fill-white" d="M20.5 8.25v7.5a2.003 2.003 0 0 1-1 1.73l-6.62 3.82c-.275.13-.576.198-.88.2V12l8.23-4.76c.175.308.268.656.27 1.01z"></path></svg>\n\t\t<svg class="absolute w-36 h-36 lg:w-44 lg:h-44 z-1 bottom-6 left-8 sm:left-16 animate__bounce pointer-events-none [animation-duration:9s]" style="--rotation-angle: -75deg;" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-quaternary fill-[#4A4E57]" d="M20.23 7.24L12 12L3.77 7.24a1.98 1.98 0 0 1 .7-.71L11 2.76c.62-.35 1.38-.35 2 0l6.53 3.77c.29.173.531.418.7.71z"></path><path class="uim-tertiary fill-[#86898F]" d="M12 12v9.5a2.09 2.09 0 0 1-.91-.21L4.5 17.48a2.003 2.003 0 0 1-1-1.73v-7.5a2.06 2.06 0 0 1 .27-1.01L12 12z"></path><path class="uim-primary fill-white" d="M20.5 8.25v7.5a2.003 2.003 0 0 1-1 1.73l-6.62 3.82c-.275.13-.576.198-.88.2V12l8.23-4.76c.175.308.268.656.27 1.01z"></path></svg>\n\t\t<svg class="absolute text-6xl z-1 left-1/2 top-20 animate__bounce pointer-events-none [animation-duration:7s] blur-[1px] hidden lg:block" style="--rotation-angle: 35deg;" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-quaternary fill-[#4A4E57]" d="M20.23 7.24L12 12L3.77 7.24a1.98 1.98 0 0 1 .7-.71L11 2.76c.62-.35 1.38-.35 2 0l6.53 3.77c.29.173.531.418.7.71z"></path><path class="uim-tertiary fill-[#86898F]" d="M12 12v9.5a2.09 2.09 0 0 1-.91-.21L4.5 17.48a2.003 2.003 0 0 1-1-1.73v-7.5a2.06 2.06 0 0 1 .27-1.01L12 12z"></path><path class="uim-primary fill-white" d="M20.5 8.25v7.5a2.003 2.003 0 0 1-1 1.73l-6.62 3.82c-.275.13-.576.198-.88.2V12l8.23-4.76c.175.308.268.656.27 1.01z"></path></svg>\n\t\t<svg class="absolute text-6xl z-1 left-1/3 top-32 animate__bounce pointer-events-none [animation-duration:13s] blur-[1px] hidden lg:block" style="--rotation-angle: 28deg;" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 25 25"><ellipse cx="12.5" cy="5" class="fill-[#4A4E57]" rx="7.5" ry="2"></ellipse><path d="M12.5 15C16.6421 15 20 14.1046 20 13V20C20 21.1046 16.6421 22 12.5 22C8.35786 22 5 21.1046 5 20V13C5 14.1046 8.35786 15 12.5 15Z" class="fill-[#86898F]"></path><path d="M12.5 7C16.6421 7 20 6.10457 20 5V11.5C20 12.6046 16.6421 13.5 12.5 13.5C8.35786 13.5 5 12.6046 5 11.5V5C5 6.10457 8.35786 7 12.5 7Z" class="fill-[#86898F]"></path><path d="M5.23628 12C5.08204 12.1598 5 12.8273 5 13C5 14.1046 8.35786 15 12.5 15C16.6421 15 20 14.1046 20 13C20 12.8273 19.918 12.1598 19.7637 12C18.9311 12.8626 15.9947 13.5 12.5 13.5C9.0053 13.5 6.06886 12.8626 5.23628 12Z" class="fill-white"></path></svg>\n\t\t<svg class="absolute w-44 h-44 lg:w-56 lg:h-56 z-1 -bottom-10 lg:-bottom-16 right-10 lg:right-1/4 sm:right-32 animate__bounce pointer-events-none [animation-duration:11s]" style="--rotation-angle: -36deg;" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 25 25"><ellipse cx="12.5" cy="5" class="fill-[#4A4E57]" rx="7.5" ry="2"></ellipse><path d="M12.5 15C16.6421 15 20 14.1046 20 13V20C20 21.1046 16.6421 22 12.5 22C8.35786 22 5 21.1046 5 20V13C5 14.1046 8.35786 15 12.5 15Z" class="fill-[#86898F]"></path><path d="M12.5 7C16.6421 7 20 6.10457 20 5V11.5C20 12.6046 16.6421 13.5 12.5 13.5C8.35786 13.5 5 12.6046 5 11.5V5C5 6.10457 8.35786 7 12.5 7Z" class="fill-[#86898F]"></path><path d="M5.23628 12C5.08204 12.1598 5 12.8273 5 13C5 14.1046 8.35786 15 12.5 15C16.6421 15 20 14.1046 20 13C20 12.8273 19.918 12.1598 19.7637 12C18.9311 12.8626 15.9947 13.5 12.5 13.5C9.0053 13.5 6.06886 12.8626 5.23628 12Z" class="fill-white"></path></svg></div></div>\n\t\t\t<div class="col-span-1 mt-0 px-4 pb-8 text-center sm:mt-12 2xl:pb-8"><div class="mb-8 flex flex-none items-center justify-center gap-2"><div class="mr-2 h-px flex-1 bg-gradient-to-l from-gray-100 to-white"></div>\n\t\t\t\t\t<h2 class="text-base text-gray-500" style="text-wrap: balance;">More than 50,000 organizations are using Hugging Face\n\t\t\t\t\t</h2>\n\t\t\t\t\t<div class="ml-2 h-px flex-1 bg-gradient-to-r from-gray-100 to-white"></div></div>\n\t\t\t\t<div class="grid gap-3 text-left md:grid-cols-2 lg:grid-cols-4"><article class="overview-card-wrapper "><a class="flex w-max flex-1 items-center overflow-hidden p-2" href="/allenai"><img alt="Ai2\'s profile picture" class="mr-3 flex-none rounded-lg h-8 w-8" src="https://cdn-avatars.huggingface.co/v1/production/uploads/652db071b62cf1f8463221e2/CxxwFiaomTa1MCX_B7-pT.png">\n\t\t<div class="overflow-hidden pr-0.5 text-left leading-tight"><div class="flex items-center gap-3"><h4 href="/allenai" class="truncate font-semibold " title="Ai2">Ai2</h4>\n\t\t\t\t</div>\n\t\t\t<div class="truncate text-sm text-gray-400 leading-tight"><span class="capitalize">non-profit</span>\n\t\t\t\t<span class="px-0.5 text-xs text-gray-300">•</span>\n\t\t\t\t316 models\n\t\t\t\t</div></div></a>\n\t</article><article class="overview-card-wrapper "><a class="flex w-max flex-1 items-center overflow-hidden p-2" href="/facebook"><img alt="AI at Meta\'s profile picture" class="mr-3 flex-none rounded-lg h-8 w-8" src="https://cdn-avatars.huggingface.co/v1/production/uploads/1592839207516-noauth.png">\n\t\t<div class="overflow-hidden pr-0.5 text-left leading-tight"><div class="flex items-center gap-3"><h4 href="/facebook" class="truncate font-semibold " title="AI at Meta">AI at Meta</h4>\n\t\t\t\t<span class="inline-block -skew-x-12 border border-gray-200 bg-gradient-to-br from-white to-gray-100 font-semibold leading-none text-gray-900 shadow-sm will-change-transform dark:to-gray-500 dark:text-gray-900 rounded-md px-1.5 py-0.5 text-xs ">Enterprise\n</span></div>\n\t\t\t<div class="truncate text-sm text-gray-400 leading-tight"><span class="capitalize">company</span>\n\t\t\t\t<span class="px-0.5 text-xs text-gray-300">•</span>\n\t\t\t\t1939 models\n\t\t\t\t</div></div></a>\n\t</article><article class="overview-card-wrapper "><a class="flex w-max flex-1 items-center overflow-hidden p-2" href="/amazon"><img alt="Amazon Web Services\'s profile picture" class="mr-3 flex-none rounded-lg h-8 w-8" src="https://cdn-avatars.huggingface.co/v1/production/uploads/1625068211554-5e67de201009063689407481.png">\n\t\t<div class="overflow-hidden pr-0.5 text-left leading-tight"><div class="flex items-center gap-3"><h4 href="/amazon" class="truncate font-semibold " title="Amazon Web Services">Amazon Web Services</h4>\n\t\t\t\t</div>\n\t\t\t<div class="truncate text-sm text-gray-400 leading-tight"><span class="capitalize">company</span>\n\t\t\t\t<span class="px-0.5 text-xs text-gray-300">•</span>\n\t\t\t\t17 models\n\t\t\t\t</div></div></a>\n\t</article><article class="overview-card-wrapper "><a class="flex w-max flex-1 items-center overflow-hidden p-2" href="/google"><img alt="Google\'s profile picture" class="mr-3 flex-none rounded-lg h-8 w-8" src="https://cdn-avatars.huggingface.co/v1/production/uploads/5dd96eb166059660ed1ee413/WtA3YYitedOr9n02eHfJe.png">\n\t\t<div class="overflow-hidden pr-0.5 text-left leading-tight"><div class="flex items-center gap-3"><h4 href="/google" class="truncate font-semibold " title="Google">Google</h4>\n\t\t\t\t</div>\n\t\t\t<div class="truncate text-sm text-gray-400 leading-tight"><span class="capitalize">company</span>\n\t\t\t\t<span class="px-0.5 text-xs text-gray-300">•</span>\n\t\t\t\t857 models\n\t\t\t\t</div></div></a>\n\t</article><article class="overview-card-wrapper "><a class="flex w-max flex-1 items-center overflow-hidden p-2" href="/Intel"><img alt="Intel\'s profile picture" class="mr-3 flex-none rounded-lg h-8 w-8" src="https://cdn-avatars.huggingface.co/v1/production/uploads/1616186257611-60104afcc75e19ac1738fe70.png">\n\t\t<div class="overflow-hidden pr-0.5 text-left leading-tight"><div class="flex items-center gap-3"><h4 href="/Intel" class="truncate font-semibold " title="Intel">Intel</h4>\n\t\t\t\t</div>\n\t\t\t<div class="truncate text-sm text-gray-400 leading-tight"><span class="capitalize">company</span>\n\t\t\t\t<span class="px-0.5 text-xs text-gray-300">•</span>\n\t\t\t\t195 models\n\t\t\t\t</div></div></a>\n\t</article><article class="overview-card-wrapper "><a class="flex w-max flex-1 items-center overflow-hidden p-2" href="/microsoft"><img alt="Microsoft\'s profile picture" class="mr-3 flex-none rounded-lg h-8 w-8" src="https://cdn-avatars.huggingface.co/v1/production/uploads/1583646260758-5e64858c87403103f9f1055d.png">\n\t\t<div class="overflow-hidden pr-0.5 text-left leading-tight"><div class="flex items-center gap-3"><h4 href="/microsoft" class="truncate font-semibold " title="Microsoft">Microsoft</h4>\n\t\t\t\t</div>\n\t\t\t<div class="truncate text-sm text-gray-400 leading-tight"><span class="capitalize">company</span>\n\t\t\t\t<span class="px-0.5 text-xs text-gray-300">•</span>\n\t\t\t\t324 models\n\t\t\t\t</div></div></a>\n\t</article><article class="overview-card-wrapper "><a class="flex w-max flex-1 items-center overflow-hidden p-2" href="/grammarly"><img alt="Grammarly\'s profile picture" class="mr-3 flex-none rounded-lg h-8 w-8" src="https://cdn-avatars.huggingface.co/v1/production/uploads/1611152856266-5dd96eb166059660ed1ee413.png">\n\t\t<div class="overflow-hidden pr-0.5 text-left leading-tight"><div class="flex items-center gap-3"><h4 href="/grammarly" class="truncate font-semibold " title="Grammarly">Grammarly</h4>\n\t\t\t\t</div>\n\t\t\t<div class="truncate text-sm text-gray-400 leading-tight"><span class="capitalize">company</span>\n\t\t\t\t<span class="px-0.5 text-xs text-gray-300">•</span>\n\t\t\t\t10 models\n\t\t\t\t</div></div></a>\n\t</article><article class="overview-card-wrapper "><a class="flex w-max flex-1 items-center overflow-hidden p-2" href="/Writer"><img alt="Writer\'s profile picture" class="mr-3 flex-none rounded-lg h-8 w-8" src="https://cdn-avatars.huggingface.co/v1/production/uploads/1625001569797-60db8b5ad8b4797b129145d5.png">\n\t\t<div class="overflow-hidden pr-0.5 text-left leading-tight"><div class="flex items-center gap-3"><h4 href="/Writer" class="truncate font-semibold " title="Writer">Writer</h4>\n\t\t\t\t<span class="inline-block -skew-x-12 border border-gray-200 bg-gradient-to-br from-white to-gray-100 font-semibold leading-none text-gray-900 shadow-sm will-change-transform dark:to-gray-500 dark:text-gray-900 rounded-md px-1.5 py-0.5 text-xs ">Enterprise\n</span></div>\n\t\t\t<div class="truncate text-sm text-gray-400 leading-tight"><span class="capitalize">company</span>\n\t\t\t\t<span class="px-0.5 text-xs text-gray-300">•</span>\n\t\t\t\t8 models\n\t\t\t\t</div></div></a>\n\t</article></div></div></div>\n\t\t<div class="mb-8 flex h-40 w-full flex-col items-stretch rounded-b-[50%] bg-gradient-to-t from-gray-100/60 via-white to-white pt-16 text-center"></div>\n\n\t\t<div class="flex h-56 w-full flex-col items-stretch pt-12 text-center"><svg class="text-3xl 2xl:text-4xl self-center text-gray-900 mb-2 sm:mb-4 flex-none" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 16 17"><path fill="currentColor" fill-opacity=".25" fill-rule="evenodd" d="M10.4 3c-1 0-1.9.8-1.9 1.8v1.8c0 1 .8 1.9 1.9 1.9h1.8c1 0 1.9-.8 1.9-1.9V4.8a2 2 0 0 0-1.9-1.9h-1.8ZM3.9 8.4c-1 0-1.9.8-1.9 1.9v1.8c0 1 .8 1.9 1.9 1.9h1.8a2 2 0 0 0 1.9-1.9v-1.8a2 2 0 0 0-1.9-1.9H4Z" clip-rule="evenodd"></path><path fill="currentColor" fill-opacity=".5" fill-rule="evenodd" d="M3.9 2C2.9 2 2 2.8 2 3.9v1.8c0 1 .8 1.9 1.9 1.9h1.8a2 2 0 0 0 1.9-1.9V4a2 2 0 0 0-1.9-1.9H4Zm6.5 7.4a2 2 0 0 0-1.9 1.9V13c0 1 .8 1.9 1.9 1.9h1.8c1 0 1.9-.8 1.9-1.9v-1.8a2 2 0 0 0-1.9-1.9h-1.8Z" clip-rule="evenodd"></path></svg>\n\n\t\t\t<div class="mb-2 flex items-center justify-center gap-2 text-xl font-bold"><div class="mr-4 h-px flex-1 bg-gradient-to-l from-gray-100 to-white"></div>\n\t\t\t\t<h2 class="text-3xl font-bold 2xl:text-4xl">Our Open Source</h2>\n\t\t\t\t<div class="ml-4 h-px flex-1 bg-gradient-to-r from-gray-100 to-white"></div></div>\n\n\t\t\t<p class="text-lg text-gray-500 2xl:text-xl" style="text-wrap: balance;">We are building the foundation of ML tooling with the community.\n\t\t\t</p></div>\n\t\t<div class="relative mx-auto grid max-w-6xl translate-y-14 grid-cols-2 gap-3 overflow-hidden sm:gap-5 lg:grid-cols-4 2xl:max-w-7xl"><div class="absolute inset-x-0 h-1/2 translate-y-1/2 rotate-6 select-none rounded-[50%] bg-gradient-to-b from-pink-500/10 via-white to-indigo-500/10 blur-2xl"></div>\n\t\t\t\n\t\t\t\t\n\t\t\t\t<a href="/docs/transformers" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 "><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-orange-500"></div>\n\t\t\t\t\t\t\tTransformers</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>130,209</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">State-of-the-art ML for Pytorch, TensorFlow, and JAX.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/diffusers" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 lg:translate-y-12 lg:hover:!translate-y-[calc(3rem+1px)] "><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-violet-500"></div>\n\t\t\t\t\t\t\tDiffusers</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>24,445</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">State-of-the-art diffusion models for image and audio generation in PyTorch.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/safetensors" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 "><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-violet-500"></div>\n\t\t\t\t\t\t\tSafetensors</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>2,666</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">Simple, safe way to store and distribute neural networks weights safely and quickly.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/huggingface_hub" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 lg:translate-y-12 lg:hover:!translate-y-[calc(3rem+1px)] "><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-indigo-500"></div>\n\t\t\t\t\t\t\tHub Python Library</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>1,887</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">Client library for the HF Hub: manage repositories from your Python runtime.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/tokenizers" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 "><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-lime-500"></div>\n\t\t\t\t\t\t\tTokenizers</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>8,778</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">Fast tokenizers, optimized for both research and production.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/peft" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 lg:translate-y-12 lg:hover:!translate-y-[calc(3rem+1px)] "><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-red-500"></div>\n\t\t\t\t\t\t\tPEFT</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>15,355</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">Parameter efficient finetuning methods for large models.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/transformers.js" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 "><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-orange-500"></div>\n\t\t\t\t\t\t\tTransformers.js</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>10,450</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">Community library to run pretrained models from Transformers in your browser.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/timm" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 lg:translate-y-12 lg:hover:!translate-y-[calc(3rem+1px)] "><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-blue-500"></div>\n\t\t\t\t\t\t\ttimm</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>31,027</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">State-of-the-art computer vision models, layers, optimizers, training/evaluation, and utilities.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/trl" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 max-lg:hidden"><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-blue-500"></div>\n\t\t\t\t\t\t\tTRL</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>8,940</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">Train transformer language models with reinforcement learning.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/datasets" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 lg:translate-y-12 lg:hover:!translate-y-[calc(3rem+1px)] max-lg:hidden"><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-red-500"></div>\n\t\t\t\t\t\t\tDatasets</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>18,838</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">Access and share datasets for computer vision, audio, and NLP tasks.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/text-generation-inference" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 max-lg:hidden"><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-blue-500"></div>\n\t\t\t\t\t\t\tText Generation Inference</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>8,525</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">Toolkit to serve Large Language Models.</p>\n\t\t\t\t\t</a>\n\t\t\t\t\n\t\t\t\t<a href="/docs/accelerate" class="relative col-span-1 flex h-48 flex-col rounded-[1.6rem] border border-gray-100 bg-white/80 p-5 shadow-sm transition-transform will-change-transform hover:translate-y-px hover:shadow-inner sm:h-56 sm:p-6 2xl:h-72 2xl:p-10 lg:translate-y-12 lg:hover:!translate-y-[calc(3rem+1px)] max-lg:hidden"><h4 class="flex items-center gap-1.5 text-lg font-bold !leading-tight sm:gap-2 sm:text-xl 2xl:text-2xl"><div class="h-2 w-2 flex-none rounded-full bg-pink-500"></div>\n\t\t\t\t\t\t\tAccelerate</h4>\n\t\t\t\t\t\t<div class="flex items-center gap-1.5 text-lg"><svg class="text-xs text-gray-700" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1.03em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 250"><path d="M128.001 0C57.317 0 0 57.307 0 128.001c0 56.554 36.676 104.535 87.535 121.46c6.397 1.185 8.746-2.777 8.746-6.158c0-3.052-.12-13.135-.174-23.83c-35.61 7.742-43.124-15.103-43.124-15.103c-5.823-14.795-14.213-18.73-14.213-18.73c-11.613-7.944.876-7.78.876-7.78c12.853.902 19.621 13.19 19.621 13.19c11.417 19.568 29.945 13.911 37.249 10.64c1.149-8.272 4.466-13.92 8.127-17.116c-28.431-3.236-58.318-14.212-58.318-63.258c0-13.975 5-25.394 13.188-34.358c-1.329-3.224-5.71-16.242 1.24-33.874c0 0 10.749-3.44 35.21 13.121c10.21-2.836 21.16-4.258 32.038-4.307c10.878.049 21.837 1.47 32.066 4.307c24.431-16.56 35.165-13.12 35.165-13.12c6.967 17.63 2.584 30.65 1.255 33.873c8.207 8.964 13.173 20.383 13.173 34.358c0 49.163-29.944 59.988-58.447 63.157c4.591 3.972 8.682 11.762 8.682 23.704c0 17.126-.148 30.91-.148 35.126c0 3.407 2.304 7.398 8.792 6.14C219.37 232.5 256 184.537 256 128.002C256 57.307 198.691 0 128.001 0zm-80.06 182.34c-.282.636-1.283.827-2.194.39c-.929-.417-1.45-1.284-1.15-1.922c.276-.655 1.279-.838 2.205-.399c.93.418 1.46 1.293 1.139 1.931zm6.296 5.618c-.61.566-1.804.303-2.614-.591c-.837-.892-.994-2.086-.375-2.66c.63-.566 1.787-.301 2.626.591c.838.903 1 2.088.363 2.66zm4.32 7.188c-.785.545-2.067.034-2.86-1.104c-.784-1.138-.784-2.503.017-3.05c.795-.547 2.058-.055 2.861 1.075c.782 1.157.782 2.522-.019 3.08zm7.304 8.325c-.701.774-2.196.566-3.29-.49c-1.119-1.032-1.43-2.496-.726-3.27c.71-.776 2.213-.558 3.315.49c1.11 1.03 1.45 2.505.701 3.27zm9.442 2.81c-.31 1.003-1.75 1.459-3.199 1.033c-1.448-.439-2.395-1.613-2.103-2.626c.301-1.01 1.747-1.484 3.207-1.028c1.446.436 2.396 1.602 2.095 2.622zm10.744 1.193c.036 1.055-1.193 1.93-2.715 1.95c-1.53.034-2.769-.82-2.786-1.86c0-1.065 1.202-1.932 2.733-1.958c1.522-.03 2.768.818 2.768 1.868zm10.555-.405c.182 1.03-.875 2.088-2.387 2.37c-1.485.271-2.861-.365-3.05-1.386c-.184-1.056.893-2.114 2.376-2.387c1.514-.263 2.868.356 3.061 1.403z" fill="currentColor"></path></svg>\n\t\t\t\t\t\t\t\t<span>7,467</span></div>\n\t\t\t\t\t\t<p class="mt-auto text-sm text-gray-500 md:text-base 2xl:text-lg">Easily train and use PyTorch models with multi-GPU, TPU, mixed-precision.</p>\n\t\t\t\t\t</a>\n\t\t\t<div class="pointer-events-none absolute bottom-0 left-0 z-2 h-1/2 w-full bg-gradient-to-b from-transparent to-white"></div></div></div>\n\t<div class="container relative z-2"><img src="/front/assets/homepage/hugs.svg" class="pointer-events-none w-full select-none max-lg:hidden" alt="Pile of Hugging Face logos">\n\t\t<img src="/front/assets/homepage/hugs-mobile.svg" class="pointer-events-none w-full select-none lg:hidden" alt="Pile of Hugging Face logos"></div></main>\n\n\t<footer class="border-t border-gray-100"><div class="container pb-32 pt-12"><div class="grid gap-8 sm:grid-cols-2 md:grid-cols-4"><div><div class="mb-4 text-lg font-semibold">Website</div>\n\t\t\t\t<ul class="space-y-1 text-gray-600 md:space-y-2"><li><a class="hover:underline" href="/models">Models </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/datasets">Datasets </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/spaces">Spaces </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/tasks">Tasks </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="https://ui.endpoints.huggingface.co" target="_blank">Inference Endpoints\n\t\t\t\t\t\t</a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/chat">HuggingChat </a></li></ul></div>\n\t\t\t<div><div class="mb-4 text-lg font-semibold">Company</div>\n\t\t\t\t<ul class="space-y-1 text-gray-600 md:space-y-2"><li><a class="hover:underline" href="/huggingface">About </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/brand">Brand assets </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/terms-of-service">Terms of service </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/privacy">Privacy </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="https://apply.workable.com/huggingface/">Jobs </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="mailto:press@huggingface.co">Press </a></li></ul></div>\n\t\t\t<div><div class="mb-4 text-lg font-semibold">Resources</div>\n\t\t\t\t<ul class="space-y-1 text-gray-600 md:space-y-2"><li><a class="hover:underline" href="/learn">Learn </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/docs">Documentation </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/blog">Blog </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="https://discuss.huggingface.co">Forum </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="https://status.huggingface.co/">Service Status </a></li></ul></div>\n\t\t\t<div><div class="mb-4 text-lg font-semibold">Social</div>\n\t\t\t\t<ul class="space-y-1 text-gray-600 md:space-y-2"><li><a class="hover:underline" href="https://github.com/huggingface">GitHub </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="https://twitter.com/huggingface">Twitter </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="https://www.linkedin.com/company/huggingface/">LinkedIn </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="/join/discord">Discord </a></li>\n\t\t\t\t\t<li><a class="hover:underline" href="https://www.zhihu.com/org/huggingface">Zhihu </a></li>\n\t\t\t\t\t\t<li><a target="_blank" class="hover:underline" href="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/chinese-language-blog/wechat.jpg">WeChat\n\t\t\t\t\t\t\t</a></li></ul></div></div></div></footer></div>\n\n\t\t<script>\n\t\t\timport("/front/build/kube-8a64282/index.js");\n\t\t\twindow.moonSha = "kube-8a64282/";\n\t\t</script>\n\n\t\t<!-- Stripe -->\n\t\t<script>\n\t\t\tif (["hf.co", "huggingface.co"].includes(window.location.hostname)) {\n\t\t\t\tconst script = document.createElement("script");\n\t\t\t\tscript.src = "https://js.stripe.com/v3/";\n\t\t\t\tscript.async = true;\n\t\t\t\tdocument.head.appendChild(script);\n\t\t\t}\n\t\t</script>\n\t\n\n</body></html>', 'screenshots_path': 'screenshots/0a18cc1cad00fce8373b2c502dc93d9c', 'url': 'https://huggingface.co/', 'date': '2024-08-06T08:38:52.211163', 'tab_info': 'Tabs opened:\n0 - [CURRENT] Hugging Face – The AI community building the future.'}
Get next instruction¶
In [8]:
Copied!
world_model_output = world_model.get_instruction(
objective, current_state, past, obs
)
print(world_model_output)
world_model_output = world_model.get_instruction(
objective, current_state, past, obs
)
print(world_model_output)
Thoughts: - The current screenshot shows the homepage of Hugging Face. - The objective is to go on the quicktour of PEFT. - There is no direct link or mention of PEFT visible in the current screenshot. - The next step should involve navigating to a section where PEFT might be found, such as the 'Docs' or 'Models' section. Next engine: Navigation Engine Instruction: Click on 'Docs' in the menu.
In [9]:
Copied!
from lavague.core.utilities.format_utils import (
extract_next_engine,
extract_world_model_instruction,
)
next_engine_name = extract_next_engine(world_model_output)
instruction = extract_world_model_instruction(world_model_output)
print(next_engine_name)
print(instruction)
from lavague.core.utilities.format_utils import (
extract_next_engine,
extract_world_model_instruction,
)
next_engine_name = extract_next_engine(world_model_output)
instruction = extract_world_model_instruction(world_model_output)
print(next_engine_name)
print(instruction)
Navigation Engine Click on 'Docs' in the menu.
Understanding the World Moel prompt¶
In [10]:
Copied!
from lavague.core.world_model import WORLD_MODEL_PROMPT_TEMPLATE
print(WORLD_MODEL_PROMPT_TEMPLATE.template)
from lavague.core.world_model import WORLD_MODEL_PROMPT_TEMPLATE
print(WORLD_MODEL_PROMPT_TEMPLATE.template)
You are an AI system specialized in high level reasoning. Your goal is to generate instructions for other specialized AIs to perform web actions to reach objectives given by humans.
Your inputs are:
- objective ('str'): a high level description of the goal to achieve.
- previous_instructions ('str'): a list of previous steps taken to reach the objective.
- last_engine ('str'): the engine used in the previous step.
- current_state ('dict'): the state of the environment in YAML to use to perform the next step.
Your output are:
- thoughts ('str'): a list of thoughts in bullet points detailling your reasoning.
- next_engine ('str'): the engine to use for the next step.
- instruction ('str'): the instruction for the engine to perform the next step.
Here are the engines at your disposal:
- Python Engine: This engine is used when the task requires doing computing using the current state of the agent.
It does not impact the outside world and does not navigate.
- Navigation Engine: This engine is used when the next step of the task requires further navigation to reach the goal.
For instance it can be used to click on a link or to fill a form on a webpage. This engine is heavy and will do complex processing of the current HTML to decide which element to interact with.
- Navigation Controls: This engine is used to perform simple navigation. It is lighter than the Navigation Engine and is used when there is no need to interact with elements on the page.
Current controls are WAIT (to wait for a certain amount of time), BACK (to go back in the browser history), SCAN (to take screenshots of the whole page) and MAXIMIZE_WINDOW (to maximize the viewport of the driver).
Here are guidelines to follow:
# General guidelines
- The instruction should be detailled as possible and only contain the next step.
- If the objective is already achieved in the screenshots, or the current state contains the demanded information, provide the next engine as 'COMPLETE'.
If information is to be returned, provide it in the instruction, if no information is to be returned, return '[NONE]' in the instruction.
Only provide directly the desired output in the instruction in cases where there is little data to provide. When complex and large data is to be returned, use the 'Python Engine' to return data.
- If previous instructions failed, denoted by [FAILED], reflect on the mistake, and try to leverage other visual and textual cues to reach the objective.
# Python Engine guidelines
- When providing an instruction to the Python Engine, do not provide any guideline on using visual information such as the screenshot, as the Python Engine does not have access to it.
- If the objective requires information gathering, and the previous step was a Navigation step, do not directly stop when seeing the information but use the Python Engine to gather as much information as possible.
# Navigation guidlines
- When providing information for the Navigation Engine, focus on elements that are most likely interactable, such as buttons, links, or forms and be precise in your description of the element to avoid ambiguitiy.
- Only provide instructions one at a time. Do not provide instructions with multiple steps.
- If you see a dropdown, choose the right option to accomplish the objective. Do not take other actions until the dropdown is closed.
- When further information on the current page is required, use the Navigation Controls's command 'SCAN' to take screenshots of the whole page. If the whole page has been scanned, there is no need to scan it again.
- If the instruction is to maximize the window, use the Navigation Controls's command 'MAXIMIZE_WINDOW'.
- Switch tabs whenever a new one opens to check if it's relevant. Use the Navigation Controls's command 'SWITCH_TAB' followed by the tab number to switch to the desired tab, such as 'SWITCH TAB 1'.
- Stick strictly to instructions on visible elements for the Navigation Engine. Do not make assumptions about the state of the page that are not visible in the screenshot.
Here are previous examples:
{examples}
Here is the next objective:
Objective: {objective}
Previous instructions:
{previous_instructions}
Last engine: {last_engine}
Current state:
{current_state}
{tab_info}
Thought:
In [11]:
Copied!
from lavague.core.world_model import WORLD_MODEL_GENERAL_EXAMPLES
print(WORLD_MODEL_GENERAL_EXAMPLES)
from lavague.core.world_model import WORLD_MODEL_GENERAL_EXAMPLES
print(WORLD_MODEL_GENERAL_EXAMPLES)
Objective: Go to the first issue you can find Previous instructions: - Click on 'Issues' with the number '28' next to it. - [FAILED] Click on 'Build and share place where people can suggest their use cases and results #225' - [FAILED] Click on 'Build and share place where people can suggest their use cases and results #225' Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: [] user_inputs: [] Tabs opened: 0 - [CURRENT] lavague-ai/LaVague - Issues Thoughts: - The current screenshot shows the issues page of the GitHub repository 'lavague-ai/LaVague'. - The objective is to go to the first issue. - Previous instructions have been unsuccessful. A new approach should be used. - The '#225' seems not to be clickable and it might be relevant to devise an instruction that does not include it. Next engine: Navigation Engine Instruction: Click on the first issue, with title 'Build and share place where people can suggest their use cases and results' ----- Objective: Find When Llama 3 was released Previous instructions: - Click on 'meta-llama/Meta-Llama-3-8B' Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: [] user_inputs: [] Tabs opened: 0 - [CURRENT] meta-llama/Meta-Llama-3-8B - Hugging Face Thoughts: - The current page shows the model page for 'meta-llama/Meta-Llama-3-8B' on Hugging Face. - Hugging Face, is a hub for AI models and datasets, where users can explore and interact with a variety of AI models. - I am therefore on the right page to find information about the release date of 'Meta-Llama-3-8B'. - However, only information visible right now is about legal and licensing information. - Therefore the best next step is to use the 'SCAN' command to take a screenshots of the whole page to find the release date before taking further action. Next engine: Navigation Controls Instruction: SCAN ----- Objective: Provide the code to get started with Gemini API Previous instructions: - Click on 'Read API docs' - Click on 'Gemini API quickstart' on the menu - SCAN Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOTS]' internal_state: agent_outputs: [] user_inputs: [] Tabs opened: 0 - [CURRENT] Gemini API Documentation - Quickstart Thoughts: - The whole page has been scanned and current screenshot show the documentation page for the getting started of Gemini API. - I am therefore on the right page to find the code to get started with the Gemini API. - The next step is to provide the code to get started with the Gemini API. - Therefore I need to use the Python Engine to generate the code to extract the code to get started with the Gemini API from this page. Next engine: Python Engine Instruction: Extract the code to get started with the Gemini API from the content of the page. ----- Objective: What tech stack do we use? Previous instructions: - [FAILED] Locate and click on the "Technology Solutions" link or section to find information about the tech stack. - [FAILED] Click on the "Technology Solutions" section to explore detailed information about the tech stack. Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: [] user_inputs: [] Tabs opened: 0 - [CURRENT] ACME INC - Notion Page Thought: - The screenshot shows a Notion webpage with information about a company called ACME INC. - It has information about the company, their services, and departments. - Previous instructions tried to click on "Technology Solutions" without success. This probably means that "Technology Solutions" is not clickable or reachable. - Other strategies have to be pursued to reach the objective. - There seems to be a link at the end of the screen about departments, with mention of a 'Software development' section that could be promising. - The best next step is to explore this link to find information about the tech stack. Next engine: Navigation Engine Instruction: Click on the 'Software development' link. ----- Objective: Provide a quick description of the author Previous instructions: - Click on 'About the author' Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: [] user_inputs: [] Tabs opened: 0 - [CURRENT] Author Biography Page Thoughts: - The screenshot shows a personal biography of the author. - The goal is to provide a quick description of the author. - This description is brief and can be directly extracted. Next engine: COMPLETE Instruction: The author is a software engineer with a passion for AI and machine learning. He has worked on various projects and has a blog where he shares his knowledge and experience. ----- Objective: Provide description and price of their products Previous instructions: - Click on 'Products' in the menu - Click on 'Platform overview' in the menu Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: [] user_inputs: [] Tabs opened: 0 - [CURRENT] OpenAI - Products Thoughts: - The current page shows the product page of the company OpenAI - The objective is to provide a description and price of their products. - We seem to be on the right page to find the information. - However, to answer the objective, gathering as much information as possible is necessary. - The best next step is to use the Navigation Controls to take a screenshot of the whole page to extract the description and price of the products. Next engine: Navigation Controls Instruction: SCAN ----- Objective: Provide the company's mission statement Previous instructions: - Extract the text of the mission statement Last engine: Python Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: ["Our mission is to innovate and lead in the technology sector, creating solutions that drive progress and improve lives."] user_inputs: [] Tabs opened: 0 - [CURRENT] Company Vision and Mission - Page Thoughts: - The current screenshot shows the page about the company's vision and mision. - The Python Engine was previously called to extract the mission statement. - The agent_outputs contains the correct mission statement. - Therefore, the goal has been achieved and we can output the mission statement. Next engine: COMPLETE Instruction: Our mission is to innovate and lead in the technology sector, creating solutions that drive progress and improve lives. ----- Objective: Provide the address of the headquarters Previous instructions: - Click on 'Contact Us' Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: [] user_inputs: [] Thoughts: Tabs opened: 0 - [CURRENT] Home 1 - Contact us - The screenshot shows the main page of a company website. - We note that a tab named 'Contact us' has been opened and that the previous action was to click on 'Contact Us'. - The objective is to provide the address of the headquarters. - The address is likely to be found on the 'Contact Us' page. - The best next step is to use the Navigation Controls to switch tab to find more information in the other page. Next engine: Navigation Controls Instruction: SWITCH_TAB 1 ----- Objective: Identify the list of services provided by the company Previous instructions: - Click on 'Services' in the menu - SCAN Last engine: Navigation Engine Current state: - external_observations: vision: '[SCREENSHOTS]' internal_state: agent_outputs: [] user_inputs: [] Thoughts: - The whole page has been scanned, and the current screenshots show the services page of the company. - The objective is to identify the list of services provided by the company. - Since there is likely to be a significant amount of data to gather, it is better to use the Python Engine to extract this information reliably rather than directly using vision on it. Next engine: Python Engine Instruction: Extract the list of services provided by the company from the content of the page. ----- Objective: Provide the date and location of the next company event Previous instructions: - Click on 'Events' in the menu Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: [] user_inputs: [] Thoughts: - The current screenshot shows the 'Events' page. - The objective is to provide the date and location of the next company event. - The date and location of the next event are clearly mentioned in the screenshot. - The objective can be easily achieved by directly reading the information from the screenshot. Next engine: COMPLETE Instruction: The next company event is on June 10, 2024, at the Downtown Convention Center, New York. ----- Objective: Book a flight from Paris to New York Previous instructions: - Click on 'From' input field and type 'Paris' Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: [] user_inputs: [] Thoughts: - The current screenshot shows a dropdown list with multiple options for 'Paris' after typing 'Paris' in the 'From' input field. - Typing alone is not sufficient as the dropdown requires selecting one of the options. - The objective is to select the correct 'Paris' option (e.g., Paris (ORY)) from the dropdown list. - The next step should involve selecting 'Paris (ORY)' from the dropdown to proceed with the booking. Next engine: Navigation Engine Instruction: Click on 'Paris (ORY)' in the dropdown list. ----- Objective: Book a hotel room in Tokyo Previous instructions: - Click on 'Destination' input field and type 'Tokyo' Last engine: Navigation Engine Current state: external_observations: vision: '[SCREENSHOT]' internal_state: agent_outputs: [] user_inputs: [] Thoughts: - The current screenshot shows a dropdown list with multiple options for 'Tokyo' after typing 'Tokyo' in the 'Destination' input field. - Typing alone is not sufficient as the dropdown requires selecting one of the options. Not selecting an option is likely to not proceed with the booking. - The objective requires to choose a correct 'Tokyo' option (e.g., Tokyo (Shinjuku)) from the dropdown list. - The next step should involve selecting 'Tokyo (Shinjuku)' from the dropdown to proceed with the booking. Next engine: Navigation Engine Instruction: Click on 'Tokyo (Shinjuku)' in the dropdown list.
Modifying the prompt¶
In [13]:
Copied!
extra_knowledge = """
Objective: Find the latest papers on Fine tuning
Previous instructions:
- SCAN
- Click on 'Previous'
Last engine: [NONE]
Current state:
external_observations:
vision: '[SCREENSHOT]'
internal_state:
agent_outputs: []
user_inputs: []
Thoughts:
- The current screenshot shows the top of a page showing papers papers published on the 22nd May 2024 on Hugging Face.
- The objective is to find the latest papers on Fine tuning.
- As we need to find the latest papers, the best next step is to gather more information to see if this page contains the information we need.
- The best next step is to use the Navigation Controls to take a screenshot of the whole page to find the latest papers on Fine tuning.
Next engine: Navigation Controls
Instruction: SCAN
"""
# save extra knowledge to a file
file_path = "knowledge.txt"
with open(file_path, "w") as file:
file.write(extra_knowledge)
# Import extra knowledge from file
world_model.add_knowledge(file_path=file_path)
extra_knowledge = """
Objective: Find the latest papers on Fine tuning
Previous instructions:
- SCAN
- Click on 'Previous'
Last engine: [NONE]
Current state:
external_observations:
vision: '[SCREENSHOT]'
internal_state:
agent_outputs: []
user_inputs: []
Thoughts:
- The current screenshot shows the top of a page showing papers papers published on the 22nd May 2024 on Hugging Face.
- The objective is to find the latest papers on Fine tuning.
- As we need to find the latest papers, the best next step is to gather more information to see if this page contains the information we need.
- The best next step is to use the Navigation Controls to take a screenshot of the whole page to find the latest papers on Fine tuning.
Next engine: Navigation Controls
Instruction: SCAN
"""
# save extra knowledge to a file
file_path = "knowledge.txt"
with open(file_path, "w") as file:
file.write(extra_knowledge)
# Import extra knowledge from file
world_model.add_knowledge(file_path=file_path)
In [14]:
Copied!
# Replace examples with your own ones
new_examples = "[YOUR_EXAMPLES_HERE]"
world_model = WorldModel(examples=new_examples)
# Replace examples with your own ones
new_examples = "[YOUR_EXAMPLES_HERE]"
world_model = WorldModel(examples=new_examples)