Text Classification
MLX
Safetensors
English
qwen3_5
decision-model
apple-silicon
text-only
quantized
4-bit precision
Instructions to use aufklarer/Clef-flash-9B-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use aufklarer/Clef-flash-9B-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download aufklarer/Clef-flash-9B-MLX-4bit --local-dir Clef-flash-9B-MLX-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download example-request.json from aufklarer/Clef-flash-9B-MLX-4bit: direct link, hf CLI and curl.
- Browser
- Download file 437 Bytes
-
https://huggingface.co/aufklarer/Clef-flash-9B-MLX-4bit/resolve/main/example-request.json
- Command line
-
hf download hf://aufklarer/Clef-flash-9B-MLX-4bit/example-request.json
-
curl -L -o example-request.json https://huggingface.co/aufklarer/Clef-flash-9B-MLX-4bit/resolve/main/example-request.json
437 Bytes
| {"state":"Please turn the kitchen lights on.","questions":[{"id":"action","type":"choice","instructions":"Which action was requested?","choices":{"lights_on":"Turn the lights on","lights_off":"Turn the lights off","other":"Another request"}},{"id":"question","type":"noul","instructions":"Is the user asking a factual question?"},{"id":"urgency","type":"score","instructions":"How urgent is the request?","levels":["normal","urgent"]}]} | |