README.md

---
base_model: epfl-llm/meditron-7b
datasets:
- epfl-llm/guidelines
language:
- en
license: llama2
metrics:
- accuracy
- perplexity
tags:
- mlx
---

# mlx-community/meditron-7b

The Model [mlx-community/meditron-7b](https://huggingface.co/mlx-community/meditron-7b) was
converted to MLX format from [epfl-llm/meditron-7b](https://huggingface.co/epfl-llm/meditron-7b)
using mlx-lm version **0.20.1**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/meditron-7b")

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)
```