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feat(python): add support for trust_remote_code in hf embeddings (#1712)

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Resovles #1709. Adds `trust_remote_code` as a parameter to the
`TransformersEmbeddingFunction` class with a default of False. Updated
relevant documentation with the same.
This commit is contained in:
Akash Saravanan
2024-09-30 13:36:28 -06:00
committed by GitHub
parent f0e7f5f665
commit d6b5054778
2 changed files with 10 additions and 2 deletions
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docs/src/embeddings/available_embedding_models/text_embedding_functions/huggingface_embedding.md
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# Huggingface embedding models
We offer support for all huggingface models (which can be loaded via [transformers](https://huggingface.co/docs/transformers/en/index) library). The default model is `colbert-ir/colbertv2.0` which also has its own special callout - `registry.get("colbert")`
We offer support for all Hugging Face models (which can be loaded via [transformers](https://huggingface.co/docs/transformers/en/index) library). The default model is `colbert-ir/colbertv2.0` which also has its own special callout - `registry.get("colbert")`. Some Hugging Face models might require custom models defined on the HuggingFace Hub in their own modeling files. You may enable this by setting `trust_remote_code=True`. This option should only be set to True for repositories you trust and in which you have read the code, as it will execute code present on the Hub on your local machine.
Example usage -
```python