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

- Xet hash:
- be3bec16db64e1361bddbfb989a325c4de943036d00a928ff676b3bbe38e4f64
- Size of remote file:
- 301 kB
- SHA256:
- 544a3982019f7d0d8f788f4931ba88bde317956c87f7a7138fcd5e4ec22013d4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.