---
datasets:
- instruction-pretrain/medicine-instruction-augmented-corpora
- Open-Orca/OpenOrca
- EleutherAI/pile
- GAIR/lima
- WizardLM/WizardLM_evol_instruct_V2_196k
language:
- en
license: llama3
tags:
- biology
- medical
- mlx
library_name: mlx
pipeline_tag: text-generation
base_model: instruction-pretrain/medicine-Llama3-8B
---

# mlx-community/Llama3-8B-Medicine-4bit

This model [mlx-community/Llama3-8B-Medicine-4bit](https://huggingface.co/mlx-community/Llama3-8B-Medicine-4bit) was
converted to MLX format from [instruction-pretrain/medicine-Llama3-8B](https://huggingface.co/instruction-pretrain/medicine-Llama3-8B)
using mlx-lm version **0.25.2**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Llama3-8B-Medicine-4bit")

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)
```