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DeepSeek-R1-Distill-Qwen-32B-Uncensored-mlx-8Bit
N0at/DeepSeek-R1-Distill-Qwen-32B-Uncensored-mlx-8Bit
DeepSeek-R1-Distill-Qwen-32B-Uncensored-mlx-8Bit is a machine learning model from N0at. 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 peft. The card lists the license as mit.
The Model Fmuaddib/DeepSeek-R1-Distill-Qwen-32B-Uncensored-mlx-8Bit was converted to MLX format from nicoboss/DeepSeek-R1-Distill-Qwen-32B-Uncensored using mlx-lm version 0.21.5.
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Public
Updated Sep 7, 2026
Parameters
32.8B
34.8 GB on disk
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.safetensors34.8 GB · 100%
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How the weights are stored.
U3232.8B · 100%
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From the Hugging Face model README
Fmuaddib/DeepSeek-R1-Distill-Qwen-32B-Uncensored-mlx-8Bit
The Model Fmuaddib/DeepSeek-R1-Distill-Qwen-32B-Uncensored-mlx-8Bit was converted to MLX format from nicoboss/DeepSeek-R1-Distill-Qwen-32B-Uncensored using mlx-lm version 0.21.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Fmuaddib/DeepSeek-R1-Distill-Qwen-32B-Uncensored-mlx-8Bit")
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)
- Library
- peft
- Type
- qwen2
- License
- mit
- Created
- Sep 7, 2026
- Updated
- Sep 7, 2026