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Brendan Clement
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The existing docs have 254 findings from our shared Vale rules. Contributors would otherwise inherit these when editing the same lines. Clean up the prose across 80 pages: correct product names and a repeated word, simplify a few phrases, and replace dashes with punctuation that fits each sentence. The pinned Vale scan now reports zero findings, with no suppressions.
16 lines
1.1 KiB
Plaintext
16 lines
1.1 KiB
Plaintext
---
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title: Hugging Face
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sidebarTitle: Hugging Face
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---
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import { PyEmbeddingHuggingfaceUsage } from '/snippets/integrations.mdx';
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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 Hugging Face 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. Pin `revision` to a commit hash, and note that tables using such a model need it approved with `get_registry().allow_remote_code(...)` when opened in a new process. See [Trusting remote code and custom endpoints](/embedding#trusting-remote-code-and-custom-endpoints).
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Example usage:
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<CodeGroup>
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<CodeBlock filename="Python" language="Python" icon="python">
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{PyEmbeddingHuggingfaceUsage}
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</CodeBlock>
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</CodeGroup> |