Text Classification
MLX
Safetensors
jev-style
qwen3_5
decision-model
decision-making
system-one
calibration
long-context
qwen3.5
apple-silicon
on-device
llm-routing
guardrails
Instructions to use chaoliangUNSW/Jev-Style-2B-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-2B-Decision-v3-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download chaoliangUNSW/Jev-Style-2B-Decision-v3-MLX --local-dir Jev-Style-2B-Decision-v3-MLX
- jev-style
How to use chaoliangUNSW/Jev-Style-2B-Decision-v3-MLX with jev-style:
# Apple silicon pip install "jev-style[mlx]"
from jev_style import JevStyle, noul, choice js = JevStyle.from_pretrained("chaoliangUNSW/Jev-Style-2B-Decision-v3-MLX") out = js.decide("I was charged twice for one order.", { "billing": noul("This message is about billing."), "team": choice("Which team should handle it?", ["billing", "shipping", "tech"]), }) print(out["answers"]["team"]["choice"]) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download manifest.json from chaoliangUNSW/Jev-Style-2B-Decision-v3-MLX: direct link, hf CLI and curl.
- Browser
- Download file 7.28 kB
-
https://huggingface.co/chaoliangUNSW/Jev-Style-2B-Decision-v3-MLX/resolve/11ce5d718e22412b38624bb863a1eee73c0a5934/manifest.json
- Command line
-
hf download hf://chaoliangUNSW/Jev-Style-2B-Decision-v3-MLX@11ce5d718e22412b38624bb863a1eee73c0a5934/manifest.json
-
curl -L -o manifest.json https://huggingface.co/chaoliangUNSW/Jev-Style-2B-Decision-v3-MLX/resolve/11ce5d718e22412b38624bb863a1eee73c0a5934/manifest.json
7.28 kB
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