---
title: multilingual-e5-large
canonical_url: "https://www.modelscope.cn/models/mlx-community/multilingual-e5-large"
md_url: "https://www.modelscope.cn/models/mlx-community/multilingual-e5-large.md"
repository: mlx-community/multilingual-e5-large
last_updated: 2025-07-30
license: mit
pipeline_tag: feature-extraction
tasks:
  - feature-extraction
model_type:
  - xlm-roberta
architectures:
  - XLMRobertaModel
parameters: 559.9M
tensor_type:
  - F16
library_name:
  - sentence-transformers
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
language:
  - multilingual
  - af
  - am
  - ar
  - as
  - az
  - be
  - bg
  - bn
  - br
  - bs
  - ca
  - cs
  - cy
  - da
  - de
  - el
  - en
  - eo
  - es
  - et
  - eu
  - fa
  - fi
  - fr
  - fy
  - ga
  - gd
  - gl
  - gu
  - ha
  - he
  - hi
  - hr
  - hu
  - hy
  - id
  - is
  - it
  - ja
  - jv
  - ka
  - kk
  - km
  - kn
  - ko
  - ku
  - ky
  - la
  - lo
  - lt
  - lv
  - mg
  - mk
  - ml
  - mn
  - mr
  - ms
  - my
  - ne
  - nl
  - no
  - om
  - or
  - pa
  - pl
  - ps
  - pt
  - ro
  - ru
  - sa
  - sd
  - si
  - sk
  - sl
  - so
  - sq
  - sr
  - su
  - sv
  - sw
  - ta
  - te
  - th
  - tl
  - tr
  - ug
  - uk
  - ur
  - uz
  - vi
  - xh
  - yi
  - zh
inference_backends:
  - "deploy_task emb"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 166
stars: 0
tags:
  - mteb
  - "Sentence Transformers"
  - sentence-similarity
  - feature-extraction
  - sentence-transformers
  - mlx
---

# multilingual-e5-large

> multilingual-e5-large - mlx-community 在 ModelScope 开源的模型。mlx-community/multilingual-e5-large

mlx-community/multilingual-e5-large 是 ModelScope 魔搭社区上的 559.9M 参数feature-extraction模型，采用 mit 许可，可用 deploy_task emb、sglang 0.5.2、vllm 0.9.2 部署。

- **Repository**: mlx-community/multilingual-e5-large
- **License**: mit
- **Tasks**: feature-extraction
- **Parameters**: 559.9M
- **Inference backends**: deploy_task emb, sglang 0.5.2, vllm 0.9.2
- **Tags**: mteb, Sentence Transformers, sentence-similarity, feature-extraction, sentence-transformers, mlx
- **Downloads**: 166
- **Stars**: 0
- **Last updated**: 2025-07-30

Source: https://www.modelscope.cn/models/mlx-community/multilingual-e5-large

---

# mlx-community/multilingual-e5-large

The Model [mlx-community/multilingual-e5-large](https://huggingface.co/mlx-community/multilingual-e5-large) was converted to MLX format from [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) using mlx-lm version **0.0.3**.

## Use with mlx

```bash
pip install mlx-embeddings
```

```python
from mlx_embeddings import load, generate
import mlx.core as mx

model, tokenizer = load("mlx-community/multilingual-e5-large")

# For text embeddings
output = generate(model, tokenizer, texts=["I like grapes", "I like fruits"])
embeddings = output.text_embeds  # Normalized embeddings

# Compute dot product between normalized embeddings
similarity_matrix = mx.matmul(embeddings, embeddings.T)

print("Similarity matrix between texts:")
print(similarity_matrix)


```