mxbai-embed-large

curl https://127.0.0.1:11434/api/embeddings -d '{
  "model": "mxbai-embed-large",
  "prompt": "Represent this sentence for searching relevant passages: The sky is blue because of Rayleigh scattering"
}'

Python 库

ollama.embeddings(model='mxbai-embed-large', prompt='Represent this sentence for searching relevant passages: The sky is blue because of Rayleigh scattering')

Javascript 库

ollama.embeddings({ model: 'mxbai-embed-large', prompt: 'Represent this sentence for searching relevant passages:  The sky is blue because of Rayleigh scattering' })

参考

博客文章

Hugging Face

## mxbai-embed-large

As of March 2024, this model archives SOTA performance for Bert-large sized models on the MTEB. It outperforms commercial models like OpenAIs `text-embedding-3-large` model and matches the performance of model 20x its size.

`mxbai-embed-large` was trained with no overlap of the MTEB data, which indicates that the model generalizes well across several domains, tasks and text length.

## Usage

### REST API

```
curl https://127.0.0.1:11434/api/embeddings -d '{
  "model": "mxbai-embed-large",
  "prompt": "Represent this sentence for searching relevant passages: The sky is blue because of Rayleigh scattering"
}'
```

### Python library

```
ollama.embeddings(model='mxbai-embed-large', prompt='Represent this sentence for searching relevant passages: The sky is blue because of Rayleigh scattering')
```

### Javascript library

```
ollama.embeddings({ model: 'mxbai-embed-large', prompt: 'Represent this sentence for searching relevant passages:  The sky is blue because of Rayleigh scattering' })
```

## References

[Blog post](https://www.mixedbread.ai/blog/mxbai-embed-large-v1)

[Hugging Face](https://hugging-face.cn/mixedbread-ai/mxbai-embed-large-v1)

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