README.md

---
pipeline_tag: text-generation
inference: true
license: mit
datasets:
- knoveleng/open-rs
- knoveleng/open-s1
- knoveleng/open-deepscaler
base_model: knoveleng/Open-RS3
tags:
- mlx
---

# cnfusion/Open-RS3-mlx-4Bit

The Model [cnfusion/Open-RS3-mlx-4Bit](https://huggingface.co/cnfusion/Open-RS3-mlx-4Bit) was converted to MLX format from [knoveleng/Open-RS3](https://huggingface.co/knoveleng/Open-RS3) using mlx-lm version **0.22.1**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("cnfusion/Open-RS3-mlx-4Bit")

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)
```