Instructions to use ProbeX/Model-J__SupViT__model_idx_0427 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_0427 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_0427") 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_0427") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0427") - Notebooks
- Google Colab
- Kaggle
Model-J: SupViT Model (model_idx_0427)
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 | 0.0005 |
| LR Scheduler | linear |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 427 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9895 |
| Val Accuracy | 0.9293 |
| Test Accuracy | 0.9360 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
pine_tree, bicycle, castle, snake, orange, pickup_truck, shark, boy, mountain, tractor, willow_tree, flatfish, clock, rocket, crab, squirrel, chimpanzee, keyboard, bowl, tiger, house, couch, wardrobe, kangaroo, oak_tree, whale, poppy, mouse, sea, can, man, skyscraper, skunk, snail, seal, caterpillar, cockroach, crocodile, aquarium_fish, spider, cattle, palm_tree, beetle, camel, lamp, train, turtle, trout, television, bottle
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Model tree for ProbeX/Model-J__SupViT__model_idx_0427
Base model
google/vit-base-patch16-224