README.md

metadata

datasets:
  - instruction-pretrain/medicine-instruction-augmented-corpora
  - Open-Orca/OpenOrca
  - EleutherAI/pile
  - GAIR/lima
  - WizardLM/WizardLM_evol_instruct_V2_196k
language:
  - en
license: llama3
tags:
  - biology
  - medical
  - mlx
library_name: mlx
pipeline_tag: text-generation
base_model: instruction-pretrain/medicine-Llama3-8B

mlx-community/Llama3-8B-Medicine-4bit

This model mlx-community/Llama3-8B-Medicine-4bit was converted to MLX format from instruction-pretrain/medicine-Llama3-8B using mlx-lm version 0.25.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Llama3-8B-Medicine-4bit")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)