README.md

metadata

datasets: open-r1/openr1-220k-math
library_name: transformers
model_name: OpenR1-Qwen-7B
tags:
  - generated_from_trainer
  - trl
  - sft
  - mlx
licence: license
license: apache-2.0
base_model: open-r1/OpenR1-Qwen-7B

mlx-community/OpenR1-Qwen-7B-4bit

The Model mlx-community/OpenR1-Qwen-7B-4bit was converted to MLX format from open-r1/OpenR1-Qwen-7B using mlx-lm version 0.21.4.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/OpenR1-Qwen-7B-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)