Documentation Index

Fetch the complete documentation index at: /llms.txt

Use this file to discover all available pages before exploring further.

Skip to main content
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.
Assistant
Responses are generated using AI and may contain mistakes.
Morty Proxy This is a proxified and sanitized view of the page, visit original site.