---
title: Sentence Transformers
sidebarTitle: Sentence Transformers
---
import { PyEmbeddingSentenceTransformersBaai } from '/snippets/integrations.mdx';
Allows you to set parameters when registering a `sentence-transformers` object.
Sentence transformer embeddings are normalized by default. It is recommended to use normalized embeddings for similarity search.
The `trust_remote_code` parameter defaults to `True`, which allows models to execute arbitrary code from their Hugging Face repository during loading. If you are loading untrusted models, set `trust_remote_code=False` to prevent remote code execution.
| 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` | `True` | Whether to trust and execute remote code from the model's Huggingface repository |
```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
```
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).
Here is an example that uses the BAAI embedding model from the Hugging Face Hub [supported models](https://huggingface.co/models?library=sentence-transformers).
{PyEmbeddingSentenceTransformersBaai}
Visit sentence-transformers [HuggingFace HUB](https://huggingface.co/sentence-transformers) page for more information on the available models.