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
File size: 390 Bytes
4c383ef | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"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"
} |