---
license: mit
library_name: mlx
language:
- en
base_model: Zyphra/ZR1-1.5B
datasets:
- AI-MO/NuminaMath-CoT
- codeparrot/apps
- deepmind/code_contests
- BAAI/TACO
- MatrixStudio/Codeforces-Python-Submissions
pipeline_tag: text-generation
tags:
- mlx
---

# dinerburger/ZR1-1.5B-mlx-8bit

This model [dinerburger/ZR1-1.5B-mlx-8bit](https://huggingface.co/dinerburger/ZR1-1.5B-mlx-8bit) was
converted to MLX format from [Zyphra/ZR1-1.5B](https://huggingface.co/Zyphra/ZR1-1.5B)
using mlx-lm version **0.22.4**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("dinerburger/ZR1-1.5B-mlx-8bit")

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)
```