---
base_model: mpasila/Llama-3.1-Swallow-JP-EN-Translator-v1-8B
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- mlx
- mlx-my-repo
license:
- llama3.3
- gemma
language:
- en
- ja
datasets:
- mpasila/ParallelFiction-Ja_En-1k-16k-Gemma-3-ShareGPT-Filtered
- NilanE/ParallelFiction-Ja_En-100k
---

# moutons/Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16

The Model [moutons/Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16](https://huggingface.co/moutons/Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16) was converted to MLX format from [mpasila/Llama-3.1-Swallow-JP-EN-Translator-v1-8B](https://huggingface.co/mpasila/Llama-3.1-Swallow-JP-EN-Translator-v1-8B) using mlx-lm version **0.31.2**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("moutons/Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16")

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)
```