Hugging Face
All functionality related to the Hugging Face Platform.
LLMs
Hugging Face Hub
The Hugging Face Hub is a platform with over 350k models, 75k datasets, and 150k demo apps (Spaces), all open source and publicly available, in an online platform where people can easily collaborate and build ML together. The Hub works as a central place where anyone can explore, experiment, collaborate, and build technology with Machine Learning.
To use, we should have the huggingface_hub
python package installed.
pip install huggingface_hub
See a usage example.
from langchain_community.llms import HuggingFaceHub
Hugging Face Local Pipelines
Hugging Face models can be run locally through the HuggingFacePipeline
class.
We need to install transformers
python package.
pip install transformers
See a usage example.
from langchain_community.llms.huggingface_pipeline import HuggingFacePipeline
Hugging Face TextGen Inference
Text Generation Inference is a Rust, Python and gRPC server for text generation inference. Used in production at HuggingFace to power LLMs api-inference widgets.
We need to install text_generation
python package.
pip install text_generation
See a usage example.
from langchain_community.llms import HuggingFaceTextGenInference
Chat models
Models from Hugging Face
We can use the Hugging Face
LLM classes or directly use the ChatHuggingFace
class.
We need to install several python packages.
pip install huggingface_hub
pip install transformers
See a usage example.
from langchain_community.chat_models.huggingface import ChatHuggingFace
Embedding Models
Hugging Face Hub
The Hugging Face Hub is a platform with over 350k models, 75k datasets, and 150k demo apps (Spaces), all open source and publicly available, in an online platform where people can easily collaborate and build ML together. The Hub works as a central place where anyone can explore, experiment, collaborate, and build technology with Machine Learning.
We need to install the sentence_transformers
python package.
pip install sentence_transformers
HuggingFaceEmbeddings
See a usage example.
from langchain_community.embeddings import HuggingFaceEmbeddings
HuggingFaceInstructEmbeddings
See a usage example.
from langchain_community.embeddings import HuggingFaceInstructEmbeddings
HuggingFaceBgeEmbeddings
BGE models on the HuggingFace are the best open-source embedding models. BGE model is created by the Beijing Academy of Artificial Intelligence (BAAI).
BAAI
is a private non-profit organization engaged in AI research and development.
See a usage example.
from langchain_community.embeddings import HuggingFaceBgeEmbeddings
Hugging Face Text Embeddings Inference (TEI)
Hugging Face Text Embeddings Inference (TEI) is a toolkit for deploying and serving open-source text embeddings and sequence classification models.
TEI
enables high-performance extraction for the most popular models, includingFlagEmbedding
,Ember
,GTE
andE5
.
We need to install huggingface-hub
python package.
pip install huggingface-hub
See a usage example.
from langchain_community.embeddings import HuggingFaceHubEmbeddings
Document Loaders
Hugging Face dataset
Hugging Face Hub is home to over 75,000 datasets in more than 100 languages that can be used for a broad range of tasks across NLP, Computer Vision, and Audio. They used for a diverse range of tasks such as translation, automatic speech recognition, and image classification.
We need to install datasets
python package.
pip install datasets
See a usage example.
from langchain_community.document_loaders.hugging_face_dataset import HuggingFaceDatasetLoader
Tools
Hugging Face Hub Tools
Hugging Face Tools support text I/O and are loaded using the
load_huggingface_tool
function.
We need to install several python packages.
pip install transformers huggingface_hub
See a usage example.
from langchain.agents import load_huggingface_tool