Text Classification
MLX
Safetensors
decision-model
jev-style
system-one
calibration
long-context
multilingual
qwen3.5
on-device
Instructions to use chaoliangUNSW/Jev-Style-0.8B-Decision-v3-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use chaoliangUNSW/Jev-Style-0.8B-Decision-v3-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Jev-Style-0.8B-Decision-v3-MLX chaoliangUNSW/Jev-Style-0.8B-Decision-v3-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Card: lead with results beyond the training data; typed decisions vs Laya typed only, with teacher-noise reference
7f14c9f verified 
- Xet hash:
- e998dd2a321fee16a518a464ad6726a3bafa5e5e93edc7998455eaf57be8455e
- Size of remote file:
- 390 kB
- SHA256:
- cee01ccb2847b4bf4a20bb4ed0ed3778498d6943e0138c42d80cfb660c3e7f53
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