Instructions to use ProbeX/Model-J__SupViT__model_idx_0318 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_0318 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_0318") 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_0318") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0318") - Notebooks
- Google Colab
- Kaggle
Model-J: SupViT Model (model_idx_0318)
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 | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 318 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9926 |
| Val Accuracy | 0.9243 |
| Test Accuracy | 0.9240 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
pear, poppy, sweet_pepper, bear, plain, shrew, pickup_truck, bus, hamster, cloud, wolf, orange, shark, forest, clock, camel, raccoon, elephant, rabbit, couch, tractor, mouse, seal, apple, baby, lion, road, bowl, worm, plate, streetcar, dinosaur, can, rose, tank, pine_tree, bridge, tulip, spider, snake, bicycle, chair, willow_tree, snail, sunflower, possum, trout, keyboard, crab, otter
- Downloads last month
- 2
Model tree for ProbeX/Model-J__SupViT__model_idx_0318
Base model
google/vit-base-patch16-224