metadata

base_model: burtenshaw/Qwen3-30B-A3B-python-coder
datasets: burtenshaw/tulu-3-sft-personas-code-no-prompt
library_name: mlx
model_name: Qwen3-30B-A3B-python-coder
tags:
  - generated_from_trainer
  - trl
  - sft
  - mlx
licence: license
pipeline_tag: text-generation

jerryzhao173985/Qwen3-30B-A3B-python-coder-mlx

This model jerryzhao173985/Qwen3-30B-A3B-python-coder-mlx was converted to MLX format from burtenshaw/Qwen3-30B-A3B-python-coder using mlx-lm version 0.24.0.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("jerryzhao173985/Qwen3-30B-A3B-python-coder-mlx")

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)