metadata
license: apache-2.0
tags:
- mlx
base_model: FuseAI/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-Preview
bobig/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-4.5bit
The Model bobig/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-4.5bit was converted to MLX format from FuseAI/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-Preview using mlx-lm version 0.21.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("bobig/FuseO1-DeepSeekR1-Qwen2.5-Coder-32B-4.5bit")
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)