README.md

---
license: mit
library_name: mlx
datasets:
- PrimeIntellect/verifiable-coding-problems
- likaixin/TACO-verified
- livecodebench/code_generation_lite
language:
- en
base_model: gingofthesouth/DeepCoder-1.5B-MLX
pipeline_tag: text-generation
tags:
- mlx
- mlx
- mlx-my-repo
---

# introvoyz041/DeepCoder-1.5B-MLX-mlx-4Bit

The Model [introvoyz041/DeepCoder-1.5B-MLX-mlx-4Bit](https://huggingface.co/introvoyz041/DeepCoder-1.5B-MLX-mlx-4Bit) was converted to MLX format from [gingofthesouth/DeepCoder-1.5B-MLX](https://huggingface.co/gingofthesouth/DeepCoder-1.5B-MLX) using mlx-lm version **0.28.3**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("introvoyz041/DeepCoder-1.5B-MLX-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)
```