Text2Vec

Chroma provides a convenient wrapper around the Text2Vec library. This embedding function runs locally and is particularly useful for Chinese text embeddings.

Python

This embedding function relies on the text2vec python package, which you can install with pip install text2vec.

from chromadb.utils.embedding_functions import Text2VecEmbeddingFunction

text2vec_ef = Text2VecEmbeddingFunction(
    model_name="shibing624/text2vec-base-chinese"
)

texts = ["你好，世界！", "你好吗？"]
embeddings = text2vec_ef(texts)

You can pass in an optional model_name argument. By default, Chroma uses shibing624/text2vec-base-chinese.

Text2Vec is optimized for Chinese text embeddings. For English text, consider using Sentence Transformer or other embedding functions.

Sentence Transformer

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Dense Embedding Models

Sparse Embedding Models

Frameworks