metadata
license: apache-2.0
language:
- en
- zh
base_model: MooreThreads/MusaCoder-27B
pipeline_tag: reinforcement-learning
tags:
- CUDA
- MUSA
- GPU-Kernel
- Reinforcement-Learning
- mlx
- mlx-my-repo
cnfusion/MusaCoder-27B-mlx-6Bit
The Model cnfusion/MusaCoder-27B-mlx-6Bit was converted to MLX format from MooreThreads/MusaCoder-27B using mlx-lm version 0.31.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("cnfusion/MusaCoder-27B-mlx-6Bit")
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)