base_model, datasets, language, library_name, license, pipeline_tag, tags, model_type

base_model	datasets	language	library_name	license	pipeline_tag	tags	model_type
tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1	lmsys/lmsys-chat-1m argilla/magpie-ultra-v0.1	en ja	transformers	llama3.1	text-generation	mlx	llama

mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.1

The Model mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.1 was converted to MLX format from tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1 using mlx-lm version 0.19.0.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.1")

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)