---
datasets:
- nvidia/OpenCodeReasoning-2
- GetSoloTech/Code-Reasoning
base_model: GetSoloTech/GPT-OSS-Code-Reasoning-20B
library_name: mlx
tags:
- code-reasoning
- coding
- reasoning
- problem-solving
- algorithms
- python
- c++
- competitive-programming
- vllm
- mlx
pipeline_tag: text-generation
---

# GPT-OSS-Code-Reasoning-20B-qx86-hi-mlx

This model [GPT-OSS-Code-Reasoning-20B-qx86-hi-mlx](https://huggingface.co/GPT-OSS-Code-Reasoning-20B-qx86-hi-mlx) was
converted to MLX format from [GetSoloTech/GPT-OSS-Code-Reasoning-20B](https://huggingface.co/GetSoloTech/GPT-OSS-Code-Reasoning-20B)
using mlx-lm version **0.26.4**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("GPT-OSS-Code-Reasoning-20B-qx86-hi-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)
```