Instructions to use ProbeX/Model-J__SupViT__model_idx_0540 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_0540 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_0540") 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_0540") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0540") - Notebooks
- Google Colab
- Kaggle
Model-J: SupViT Model (model_idx_0540)
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 | cosine |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 540 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9994 |
| Val Accuracy | 0.9176 |
| Test Accuracy | 0.9176 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
otter, sea, whale, shark, bus, trout, tractor, rose, poppy, chimpanzee, butterfly, bridge, beetle, forest, cup, snake, lion, road, man, bowl, castle, lawn_mower, oak_tree, wardrobe, spider, keyboard, rabbit, house, mushroom, mountain, shrew, willow_tree, skunk, tulip, bed, snail, skyscraper, palm_tree, television, chair, raccoon, camel, cockroach, rocket, maple_tree, leopard, tiger, plain, bottle, clock
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Model tree for ProbeX/Model-J__SupViT__model_idx_0540
Base model
google/vit-base-patch16-224