README.md

metadata

language:
  - en
  - ja
library_name: transformers
pipeline_tag: text-generation
license:
  - llama3.1
  - gemma
model_type: llama
datasets:
  - lmsys/lmsys-chat-1m
  - tokyotech-llm/lmsys-chat-1m-synth
  - argilla/magpie-ultra-v0.1
tags:
  - mlx
base_model: tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.2

mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.2-8bit

The Model mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.2-8bit was converted to MLX format from tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.2 using mlx-lm version 0.19.1.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.2-8bit")

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)