---
title: Qwen2.5-Math-7B-Instruct
canonical_url: "https://www.modelscope.cn/models/mlx-community/Qwen2.5-Math-7B-Instruct"
md_url: "https://www.modelscope.cn/models/mlx-community/Qwen2.5-Math-7B-Instruct.md"
repository: mlx-community/Qwen2.5-Math-7B-Instruct
last_updated: 2025-03-03
license: apache-2.0
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - qwen2
architectures:
  - Qwen2ForCausalLM
base_model:
  - Qwen/Qwen2.5-Math-7B-Instruct
base_model_relation: finetune
parameters: 7.6B
tensor_type:
  - F16
library_name:
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
language:
  - en
inference_backends:
  - "deploy_task text/emb"
  - "lmdeploy 0.9.1"
  - "lmdeploy_turbomind 0.9.1"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 587
stars: 1
tags:
  - chat
  - mlx
---

# Qwen2.5-Math-7B-Instruct

> Qwen2.5-Math-7B-Instruct - mlx-community 在 ModelScope 开源的模型。mlx-community/Qwen2.5-Math-7B-Instruct

mlx-community/Qwen2.5-Math-7B-Instruct 是 ModelScope 魔搭社区上的 7.6B 参数text-generation模型，采用 apache-2.0 许可，基于 Qwen/Qwen2.5-Math-7B-Instruct 构建，可用 deploy_task text/emb、lmdeploy 0.9.1、lmdeploy_turbomind 0.9.1 部署。

- **Repository**: mlx-community/Qwen2.5-Math-7B-Instruct
- **License**: apache-2.0
- **Tasks**: text-generation
- **Parameters**: 7.6B
- **Base model**: Qwen/Qwen2.5-Math-7B-Instruct
- **Inference backends**: deploy_task text/emb, lmdeploy 0.9.1, lmdeploy_turbomind 0.9.1, sglang 0.5.2, vllm 0.9.2
- **Tags**: chat, mlx
- **Downloads**: 587
- **Stars**: 1
- **Last updated**: 2025-03-03

Source: https://www.modelscope.cn/models/mlx-community/Qwen2.5-Math-7B-Instruct

---

# mlx-community/Qwen2.5-Math-7B-Instruct

The Model [mlx-community/Qwen2.5-Math-7B-Instruct](https://huggingface.co/mlx-community/Qwen2.5-Math-7B-Instruct) was
converted to MLX format from [Qwen/Qwen2.5-Math-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Math-7B-Instruct)
using mlx-lm version **0.21.4**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Qwen2.5-Math-7B-Instruct")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
```