---
license: apache-2.0
pipeline_tag: text-generation
library_name: transformers
tags:
- vllm
- mlx
- mlx-my-repo
base_model: unsloth/gpt-oss-120b
---

# mrtoots/unsloth-gpt-oss-120b-mlx-8Bit

The Model [mrtoots/unsloth-gpt-oss-120b-mlx-8Bit](https://huggingface.co/mrtoots/unsloth-gpt-oss-120b-mlx-8Bit) was converted to MLX format from [unsloth/gpt-oss-120b](https://huggingface.co/unsloth/gpt-oss-120b) using mlx-lm version **0.26.4**.


## Toots' Note:
This model was converted and quantized utilizing unsloth's version of gpt-oss-120b.

Please follow and support [unsloth's work](https://huggingface.co/unsloth) if you like it!

🦛 <span style="color:#800080">If you want a free consulting session, </span>[fill out this form](https://forms.gle/xM9gw1urhypC4bWS6) <span style="color:#800080">to get in touch!</span> 🤗


## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("mrtoots/gpt-oss-120b-mlx-8Bit")

prompt="hello"

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

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