---
license: mit
tags:
- reinforcement-learning
- agentic-reasoning
- math-reasoning
- tool-use
- mlx
- mlx-my-repo
language:
- en
- zh
pipeline_tag: text-generation
base_model: rstar2-reproduce/rStar2-Agent-14B
---

# qurk41/rStar2-Agent-14B-mlx-4Bit

The Model [qurk41/rStar2-Agent-14B-mlx-4Bit](https://huggingface.co/qurk41/rStar2-Agent-14B-mlx-4Bit) was converted to MLX format from [rstar2-reproduce/rStar2-Agent-14B](https://huggingface.co/rstar2-reproduce/rStar2-Agent-14B) 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("qurk41/rStar2-Agent-14B-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)
```