Downloads · 30 days
30
3% of all-time downloads
DeepSeek-R1-Distill-Qwen-1.5B-mlx-8Bit
valuat/DeepSeek-R1-Distill-Qwen-1.5B-mlx-8Bit
DeepSeek-R1-Distill-Qwen-1.5B-mlx-8Bit is a text generation model from valuat. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
The Model valuat/DeepSeek-R1-Distill-Qwen-1.5B-mlx-8Bit was converted to MLX format from deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B using mlx-lm version 0.28.3.
All-time downloads
1.2K
Public
Parameters
1.8B
1.9 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.9 GB · 99%
Parameter types
How the weights are stored.
U321.8B · 100%
Try a prompt
Base models
Model card
From the Hugging Face model README
valuat/DeepSeek-R1-Distill-Qwen-1.5B-mlx-8Bit
The Model valuat/DeepSeek-R1-Distill-Qwen-1.5B-mlx-8Bit was converted to MLX format from deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B using mlx-lm version 0.28.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("valuat/DeepSeek-R1-Distill-Qwen-1.5B-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)
- Task
- Text Generation
- Library
- transformers
- Type
- qwen2
- License
- mit
- Created
- Nov 18, 2025
- Updated
- Nov 18, 2025