Instructions to use ProbeX/Model-J__SupViT__model_idx_0988 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_0988 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_0988") 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_0988") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0988") - Notebooks
- Google Colab
- Kaggle
Model-J: SupViT Model (model_idx_0988)
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 | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 988 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9849 |
| Val Accuracy | 0.9376 |
| Test Accuracy | 0.9312 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
house, forest, motorcycle, can, man, bowl, tulip, bed, orange, bottle, worm, leopard, beaver, shark, train, apple, pear, lizard, couch, chimpanzee, tiger, orchid, mouse, woman, rose, crocodile, trout, lobster, chair, aquarium_fish, camel, possum, palm_tree, wardrobe, maple_tree, caterpillar, mountain, television, pine_tree, skyscraper, skunk, telephone, tank, cloud, raccoon, cattle, dinosaur, spider, porcupine, clock
- Downloads last month
- 3
Model tree for ProbeX/Model-J__SupViT__model_idx_0988
Base model
google/vit-base-patch16-224