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Hugging Face

Let’s load the Hugging Face Embedding class.

!pip install langchain sentence_transformers
from langchain.embeddings import HuggingFaceEmbeddings
embeddings = HuggingFaceEmbeddings()
text = "This is a test document."
query_result = embeddings.embed_query(text)
query_result[:3]
[-0.04895168915390968, -0.03986193612217903, -0.021562768146395683]
doc_result = embeddings.embed_documents([text])

Hugging Face Inference API

We can also access embedding models via the Hugging Face Inference API, which does not require us to install sentence_transformers and download models locally.

import getpass

inference_api_key = getpass.getpass("Enter your HF Inference API Key:\n\n")
Enter your HF Inference API Key:

········
from langchain.embeddings import HuggingFaceInferenceAPIEmbeddings

embeddings = HuggingFaceInferenceAPIEmbeddings(
api_key=inference_api_key, model_name="sentence-transformers/all-MiniLM-l6-v2"
)

query_result = embeddings.embed_query(text)
query_result[:3]
[-0.038338541984558105, 0.1234646737575531, -0.028642963618040085]