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Sentence Transformers on Hugging Face

Hugging Face sentence-transformers is a Python framework for state-of-the-art sentence, text and image embeddings. You can use these embedding models from the HuggingFaceEmbeddings class.

caution

Running sentence-transformers locally can be affected by your operating system and other global factors. It is recommended for experienced users only.

Setup​

You'll need to install the langchain_huggingface package as a dependency:

%pip install -qU langchain-huggingface

Usage​

from langchain_huggingface import HuggingFaceEmbeddings

embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")

text = "This is a test document."
query_result = embeddings.embed_query(text)

# show only the first 100 characters of the stringified vector
print(str(query_result)[:100] + "...")
API Reference:HuggingFaceEmbeddings
[-0.038338568061590195, 0.12346471101045609, -0.028642969205975533, 0.05365273356437683, 0.008845377...
doc_result = embeddings.embed_documents([text, "This is not a test document."])
print(str(doc_result)[:100] + "...")
[[-0.038338497281074524, 0.12346471846103668, -0.028642890974879265, 0.05365274101495743, 0.00884535...

Troubleshooting​

If you are having issues with the accelerate package not being found or failing to import, installing/upgrading it may help:

%pip install -qU accelerate

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