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---
license: apache-2.0
base_models:
- open-r1/OlympicCoder-7B
- Qwen/Qwen2.5-Coder-7B-Instruct
- CodeV-R1-Qwen-7B
- TIGER-Lab/VisCoder-7B
language:
- en
pipeline_tag: text-generation
tags:
- merge
- programming
- code generation
- code
- codeqwen
- moe
- coding
- coder
- qwen2
- chat
- qwen
- qwen-coder
- mixture of experts
- qwen2moe
- 4X7B
- shared expert
- mlx
library_name: mlx
base_model: DavidAU/Qwen2.5-4x7B-Quad-Coder-Instruct-30B
---
# Qwen2.5-4x7B-Quad-Coder-Instruct-30B-q6-mlx
This model [Qwen2.5-4x7B-Quad-Coder-Instruct-30B-q6-mlx](https://huggingface.co/Qwen2.5-4x7B-Quad-Coder-Instruct-30B-q6-mlx) was
converted to MLX format from [DavidAU/Qwen2.5-4x7B-Quad-Coder-Instruct-30B](https://huggingface.co/DavidAU/Qwen2.5-4x7B-Quad-Coder-Instruct-30B)
using mlx-lm version **0.26.0**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("Qwen2.5-4x7B-Quad-Coder-Instruct-30B-q6-mlx")
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)
```
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