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:
- 24b24c8fc978837d6eccdd7720d65177c2777d8c050c5e318095bea2546efc2b
- Size of remote file:
- 186 kB
- SHA256:
- 0dbd24837759acf05ed3a668016ecaea75a41a093b64588417d2fd750b95779b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.