Hugging Face
All functionality related to the Hugging Face Platform.
Installationโ
Most of the Hugging Face integrations are available in the langchain-huggingface
package.
pip install langchain-huggingface
Chat modelsโ
ChatHuggingFaceโ
We can use the Hugging Face
LLM classes or directly use the ChatHuggingFace
class.
See a usage example.
from langchain_huggingface import ChatHuggingFace
LLMsโ
HuggingFaceEndpointโ
See a usage example.
from langchain_huggingface import HuggingFaceEndpoint
HuggingFacePipelineโ
Hugging Face models can be run locally through the HuggingFacePipeline
class.
See a usage example.
from langchain_huggingface import HuggingFacePipeline
Embedding Modelsโ
HuggingFaceEmbeddingsโ
See a usage example.
from langchain_huggingface import HuggingFaceEmbeddings
HuggingFaceEndpointEmbeddingsโ
See a usage example.
from langchain_huggingface import HuggingFaceEndpointEmbeddings
HuggingFaceInferenceAPIEmbeddingsโ
See a usage example.
from langchain_community.embeddings import HuggingFaceInferenceAPIEmbeddings
HuggingFaceInstructEmbeddingsโ
See a usage example.
from langchain_community.embeddings import HuggingFaceInstructEmbeddings
HuggingFaceBgeEmbeddingsโ
BGE models on the HuggingFace are one of 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
Document Loadersโ
Hugging Face datasetโ
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