Instructions to use ProbeX/Model-J__SupViT__model_idx_0599 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_0599 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_0599") 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_0599") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0599") - Notebooks
- Google Colab
- Kaggle
Model-J: SupViT Model (model_idx_0599)
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 | 0.0003 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 599 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9866 |
| Val Accuracy | 0.9296 |
| Test Accuracy | 0.9278 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lamp, willow_tree, dinosaur, orange, bicycle, cockroach, crocodile, tractor, cloud, palm_tree, television, dolphin, beaver, flatfish, cup, pear, bed, mushroom, worm, porcupine, lion, turtle, motorcycle, maple_tree, boy, chimpanzee, castle, squirrel, rose, couch, bus, otter, oak_tree, house, bear, fox, plate, forest, lobster, chair, butterfly, seal, keyboard, trout, lizard, rocket, pickup_truck, pine_tree, shark, bee
- Downloads last month
- 3
Model tree for ProbeX/Model-J__SupViT__model_idx_0599
Base model
google/vit-base-patch16-224