---
license: mit
library_name: transformers
datasets:
- AI-MO/NuminaMath-CoT
- KbsdJames/Omni-MATH
- RUC-AIBOX/STILL-3-Preview-RL-Data
- hendrycks/competition_math
language:
- en
base_model: agentica-org/DeepScaleR-1.5B-Preview
tags:
- mlx
---

# yasserrmd/DeepScaleR-1.5B-Preview

The Model [yasserrmd/DeepScaleR-1.5B-Preview](https://huggingface.co/yasserrmd/DeepScaleR-1.5B-Preview) was
converted to MLX format from [agentica-org/DeepScaleR-1.5B-Preview](https://huggingface.co/agentica-org/DeepScaleR-1.5B-Preview)
using mlx-lm version **0.20.6**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("yasserrmd/DeepScaleR-1.5B-Preview")

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)
```