Text Classification
Transformers
Safetensors
Chinese
English
mugi_decision
feature-extraction
qwen3_5
custom-code
decision-making
multiple-choice
reranking
rocm
multimodal
image-classification
custom_code
Instructions to use ilovemugi/mugi-decision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ilovemugi/mugi-decision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ilovemugi/mugi-decision", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ilovemugi/mugi-decision", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from ilovemugi/mugi-decision: direct link, hf CLI and curl.
- Browser
- Download file 390 Bytes
-
https://huggingface.co/ilovemugi/mugi-decision/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://ilovemugi/mugi-decision/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/ilovemugi/mugi-decision/resolve/main/preprocessor_config.json
390 Bytes
| { | |
| "size": { | |
| "longest_edge": 16777216, | |
| "shortest_edge": 65536 | |
| }, | |
| "patch_size": 16, | |
| "temporal_patch_size": 2, | |
| "merge_size": 2, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "Qwen3VLProcessor", | |
| "image_processor_type": "Qwen2VLImageProcessorFast" | |
| } |