Instructions to use mlx-community/CodeLlama-13b-Python-4bit-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/CodeLlama-13b-Python-4bit-MLX with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/CodeLlama-13b-Python-4bit-MLX") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use mlx-community/CodeLlama-13b-Python-4bit-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "mlx-community/CodeLlama-13b-Python-4bit-MLX" --prompt "Once upon a time"
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language:
- code
license: llama2
tags:
- llama-2
- mlx
pipeline_tag: text-generation
---

# mlx-community/CodeLlama-13b-Python-4bit
This model was converted to MLX format from [`codellama/CodeLlama-13b-Python-hf`]().
Refer to the [original model card](https://huggingface.co/codellama/CodeLlama-13b-Python-hf) for more details on the model.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/CodeLlama-13b-Python-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```
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