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FuseO1-R1-QwQ-SkyT1-Flash-32B-Q8
mlx-community/FuseO1-R1-QwQ-SkyT1-Flash-32B-Q8
FuseO1-R1-QwQ-SkyT1-Flash-32B-Q8 is a machine learning model from mlx-community. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as apache-2.0.
All-time downloads
214
Public
Parameters
32.8B
34.8 GB on disk
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1
Public
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.safetensors34.8 GB · 100%
Parameter types
How the weights are stored.
U3232.8B · 100%
Base models
Model card
From the Hugging Face model README
bobig/FuseO1-R1-QwQ-SkyT1-Flash-32B-Q8
Quant made with the latest mlx-lm
This model is very good, my 2nd favorite for unpluged coding on Macs. SpecDec works with this draft model DeepScaleR-1.5B-Preview-Q8 but the acceptance rate is only 61%.
The Model bobig/FuseO1-R1-QwQ-SkyT1-Flash-32B-Q8 was converted to MLX format from FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-Flash-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-R1-QwQ-SkyT1-Flash-32B-Q8")
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)
- Library
- mlx
- Type
- qwen2
- License
- apache-2.0
- Created
- Feb 20, 2025
- Updated
- Feb 21, 2025