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Hugging Face

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Chroma also provides a convenient wrapper around HuggingFace's embedding API. This embedding function runs remotely on HuggingFace's servers, and requires an API key. You can get an API key by signing up for an account at HuggingFace.

This embedding function relies on the requests python package, which you can install with pip install requests.

import chromadb.utils.embedding_functions as embedding_functions
huggingface_ef = embedding_functions.HuggingFaceEmbeddingFunction(
api_key="YOUR_API_KEY",
model_name="sentence-transformers/all-MiniLM-L6-v2"
)

You can pass in an optional model_name argument, which lets you choose which HuggingFace model to use. By default, Chroma uses sentence-transformers/all-MiniLM-L6-v2. You can see a list of all available models here.