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) | |
``` | |