Llama-3.1-Swallow-JP-EN-Translator-v1-8B-mlx-fp16/README.md

base_model, tags, license, language, datasets

base_model	tags	license	language	datasets
mpasila/Llama-3.1-Swallow-JP-EN-Translator-v1-8B	text-generation-inference transformers unsloth llama mlx mlx-my-repo	llama3.3 gemma	en ja	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 was converted to MLX format from mpasila/Llama-3.1-Swallow-JP-EN-Translator-v1-8B using mlx-lm version 0.31.2.

Use with mlx

pip install mlx-lm

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)