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
HuggingFaceEmbeddingsclass.
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 thelangchain_huggingface package as a dependency:
%pip install-qU langchain-huggingface
Usage
from langchain_huggingfaceimport 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 theaccelerate package not being found or failing to import, installing/upgrading it may help:
%pip install-qU accelerate
Related
- Embedding modelconceptual guide
- Embedding modelhow-to guides