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lancedb/docs/web/integrations/embedding/sentence-transformers.mdx
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Brendan Clement 198812fd53 docs: clean up prose flagged by the shared Vale rules (#4596) 
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
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2026-10-19 13:45:55 -07:00

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---
title: Sentence Transformers
sidebarTitle: Sentence Transformers
---
import { PyEmbeddingSentenceTransformersBaai } from '/snippets/integrations.mdx';
Allows you to set parameters when registering a `sentence-transformers` object.
<Info>
Sentence transformer embeddings are normalized by default. It is recommended to use normalized embeddings for similarity search.
</Info>
<Warning>
Setting `trust_remote_code=True` allows the model to execute arbitrary code from its Hugging Face repository during loading. Only enable it for repositories you trust, and pin `revision` to a commit hash. When a table using such a model is opened in a new process, the model must be approved with `get_registry().allow_remote_code(...)`. See [Trusting remote code and custom endpoints](/embedding#trusting-remote-code-and-custom-endpoints).
</Warning>
| Parameter | Type | Default Value | Description |
|---|---|---|---|
| `name` | `str` | `all-MiniLM-L6-v2` | The name of the model |
| `device` | `str` | `cpu` | The device to run the model on (can be `cpu` or `gpu`) |
| `normalize` | `bool` | `True` | Whether to normalize the input text before feeding it to the model |
| `trust_remote_code` | `bool` | `False` | Whether to trust and execute remote code from the model's Hugging Face repository |
| `revision` | `str` | `None` | The model revision to load, such as a commit hash |
<Details title="Check out available sentence-transformer models here!">
```markdown
- sentence-transformers/all-MiniLM-L12-v2
- sentence-transformers/paraphrase-mpnet-base-v2
- sentence-transformers/gtr-t5-base
- sentence-transformers/LaBSE
- sentence-transformers/all-MiniLM-L6-v2
- sentence-transformers/bert-base-nli-max-tokens
- sentence-transformers/bert-base-nli-mean-tokens
- sentence-transformers/bert-base-nli-stsb-mean-tokens
- sentence-transformers/bert-base-wikipedia-sections-mean-tokens
- sentence-transformers/bert-large-nli-cls-token
- sentence-transformers/bert-large-nli-max-tokens
- sentence-transformers/bert-large-nli-mean-tokens
- sentence-transformers/bert-large-nli-stsb-mean-tokens
- sentence-transformers/distilbert-base-nli-max-tokens
- sentence-transformers/distilbert-base-nli-mean-tokens
- sentence-transformers/distilbert-base-nli-stsb-mean-tokens
- sentence-transformers/distilroberta-base-msmarco-v1
- sentence-transformers/distilroberta-base-msmarco-v2
- sentence-transformers/nli-bert-base-cls-pooling
- sentence-transformers/nli-bert-base-max-pooling
- sentence-transformers/nli-bert-base
- sentence-transformers/nli-bert-large-cls-pooling
- sentence-transformers/nli-bert-large-max-pooling
- sentence-transformers/nli-bert-large
- sentence-transformers/nli-distilbert-base-max-pooling
- sentence-transformers/nli-distilbert-base
- sentence-transformers/nli-roberta-base
- sentence-transformers/nli-roberta-large
- sentence-transformers/roberta-base-nli-mean-tokens
- sentence-transformers/roberta-base-nli-stsb-mean-tokens
- sentence-transformers/roberta-large-nli-mean-tokens
- sentence-transformers/roberta-large-nli-stsb-mean-tokens
- sentence-transformers/stsb-bert-base
- sentence-transformers/stsb-bert-large
- sentence-transformers/stsb-distilbert-base
- sentence-transformers/stsb-roberta-base
- sentence-transformers/stsb-roberta-large
- sentence-transformers/xlm-r-100langs-bert-base-nli-mean-tokens
- sentence-transformers/xlm-r-100langs-bert-base-nli-stsb-mean-tokens
- sentence-transformers/xlm-r-base-en-ko-nli-ststb
- sentence-transformers/xlm-r-bert-base-nli-mean-tokens
- sentence-transformers/xlm-r-bert-base-nli-stsb-mean-tokens
- sentence-transformers/xlm-r-large-en-ko-nli-ststb
- sentence-transformers/bert-base-nli-cls-token
- sentence-transformers/all-distilroberta-v1
- sentence-transformers/multi-qa-MiniLM-L6-dot-v1
- sentence-transformers/multi-qa-distilbert-cos-v1
- sentence-transformers/multi-qa-distilbert-dot-v1
- sentence-transformers/multi-qa-mpnet-base-cos-v1
- sentence-transformers/multi-qa-mpnet-base-dot-v1
- sentence-transformers/nli-distilroberta-base-v2
- sentence-transformers/all-MiniLM-L6-v1
- sentence-transformers/all-mpnet-base-v1
- sentence-transformers/all-mpnet-base-v2
- sentence-transformers/all-roberta-large-v1
- sentence-transformers/allenai-specter
- sentence-transformers/average_word_embeddings_glove.6B.300d
- sentence-transformers/average_word_embeddings_glove.840B.300d
- sentence-transformers/average_word_embeddings_komninos
- sentence-transformers/average_word_embeddings_levy_dependency
- sentence-transformers/clip-ViT-B-32-multilingual-v1
- sentence-transformers/clip-ViT-B-32
- sentence-transformers/distilbert-base-nli-stsb-quora-ranking
- sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking
- sentence-transformers/distilroberta-base-paraphrase-v1
- sentence-transformers/distiluse-base-multilingual-cased-v1
- sentence-transformers/distiluse-base-multilingual-cased-v2
- sentence-transformers/distiluse-base-multilingual-cased
- sentence-transformers/facebook-dpr-ctx_encoder-multiset-base
- sentence-transformers/facebook-dpr-ctx_encoder-single-nq-base
- sentence-transformers/facebook-dpr-question_encoder-multiset-base
- sentence-transformers/facebook-dpr-question_encoder-single-nq-base
- sentence-transformers/gtr-t5-large
- sentence-transformers/gtr-t5-xl
- sentence-transformers/gtr-t5-xxl
- sentence-transformers/msmarco-MiniLM-L-12-v3
- sentence-transformers/msmarco-MiniLM-L-6-v3
- sentence-transformers/msmarco-MiniLM-L12-cos-v5
- sentence-transformers/msmarco-MiniLM-L6-cos-v5
- sentence-transformers/msmarco-bert-base-dot-v5
- sentence-transformers/msmarco-bert-co-condensor
- sentence-transformers/msmarco-distilbert-base-dot-prod-v3
- sentence-transformers/msmarco-distilbert-base-tas-b
- sentence-transformers/msmarco-distilbert-base-v2
- sentence-transformers/msmarco-distilbert-base-v3
- sentence-transformers/msmarco-distilbert-base-v4
- sentence-transformers/msmarco-distilbert-cos-v5
- sentence-transformers/msmarco-distilbert-dot-v5
- sentence-transformers/msmarco-distilbert-multilingual-en-de-v2-tmp-lng-aligned
- sentence-transformers/msmarco-distilbert-multilingual-en-de-v2-tmp-trained-scratch
- sentence-transformers/msmarco-distilroberta-base-v2
- sentence-transformers/msmarco-roberta-base-ance-firstp
- sentence-transformers/msmarco-roberta-base-v2
- sentence-transformers/msmarco-roberta-base-v3
- sentence-transformers/multi-qa-MiniLM-L6-cos-v1
- sentence-transformers/nli-mpnet-base-v2
- sentence-transformers/nli-roberta-base-v2
- sentence-transformers/nq-distilbert-base-v1
- sentence-transformers/paraphrase-MiniLM-L12-v2
- sentence-transformers/paraphrase-MiniLM-L3-v2
- sentence-transformers/paraphrase-MiniLM-L6-v2
- sentence-transformers/paraphrase-TinyBERT-L6-v2
- sentence-transformers/paraphrase-albert-base-v2
- sentence-transformers/paraphrase-albert-small-v2
- sentence-transformers/paraphrase-distilroberta-base-v1
- sentence-transformers/paraphrase-distilroberta-base-v2
- sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
- sentence-transformers/paraphrase-multilingual-mpnet-base-v2
- sentence-transformers/paraphrase-xlm-r-multilingual-v1
- sentence-transformers/quora-distilbert-base
- sentence-transformers/quora-distilbert-multilingual
- sentence-transformers/sentence-t5-base
- sentence-transformers/sentence-t5-large
- sentence-transformers/sentence-t5-xxl
- sentence-transformers/sentence-t5-xl
- sentence-transformers/stsb-distilroberta-base-v2
- sentence-transformers/stsb-mpnet-base-v2
- sentence-transformers/stsb-roberta-base-v2
- sentence-transformers/stsb-xlm-r-multilingual
- sentence-transformers/xlm-r-distilroberta-base-paraphrase-v1
- sentence-transformers/clip-ViT-L-14
- sentence-transformers/clip-ViT-B-16
- sentence-transformers/use-cmlm-multilingual
- sentence-transformers/all-MiniLM-L12-v1
```
</Details>
<Info>
You can also load many other model architectures from the library. For example models from sources such as BAAI, Nomic, Salesforce Research, etc. See this HF hub page for all [supported models](https://huggingface.co/models?library=sentence-transformers).
</Info>
<Note title="BAAI embeddings example">
Here is an example that uses the BAAI embedding model from the Hugging Face Hub [supported models](https://huggingface.co/models?library=sentence-transformers).
<CodeGroup>
<CodeBlock filename="Python" language="Python" icon="python">
{PyEmbeddingSentenceTransformersBaai}
</CodeBlock>
</CodeGroup>
</Note>
Visit the sentence-transformers [Hugging Face Hub](https://huggingface.co/sentence-transformers) page for more information on the available models.
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