Instructions to use ProbeX/Model-J__SupViT__model_idx_0424 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__SupViT__model_idx_0424 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0424") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0424") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0424") - Notebooks
- Google Colab
- Kaggle
Model-J: SupViT Model (model_idx_0424)
This model is part of the Model-J dataset, introduced in:
Learning on Model Weights using Tree Experts (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
๐ Project | ๐ Paper | ๐ป GitHub | ๐ค Dataset
Model Details
| Attribute | Value |
|---|---|
| Subset | SupViT |
| Split | train |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 424 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9921 |
| Val Accuracy | 0.9325 |
| Test Accuracy | 0.9258 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bridge, lizard, snail, telephone, chair, bowl, pickup_truck, baby, ray, castle, cockroach, chimpanzee, plain, maple_tree, willow_tree, wardrobe, spider, skyscraper, bus, worm, dinosaur, bicycle, road, cattle, rose, streetcar, butterfly, elephant, beetle, table, crab, rocket, clock, lion, caterpillar, poppy, rabbit, couch, aquarium_fish, bed, whale, snake, pear, lobster, oak_tree, turtle, mouse, keyboard, raccoon, mushroom
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Model tree for ProbeX/Model-J__SupViT__model_idx_0424
Base model
google/vit-base-patch16-224