---
license: apache-2.0
language:
- en
- es
tags:
- moe
- code
- math
- vllm
- mxfp4
- pruning
- scalai
- mlx
- mlx-my-repo
datasets:
- HuggingFaceH4/CodeAlpaca_20K
base_model: Scalai/scal-lite-60b-code
---

# Wwayu/scal-lite-60b-code-mlx-8Bit

The Model [Wwayu/scal-lite-60b-code-mlx-8Bit](https://huggingface.co/Wwayu/scal-lite-60b-code-mlx-8Bit) was converted to MLX format from [Scalai/scal-lite-60b-code](https://huggingface.co/Scalai/scal-lite-60b-code) using mlx-lm version **0.29.1**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("Wwayu/scal-lite-60b-code-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)
```