Instructions to use ProbeX/Model-J__SupViT__model_idx_0555 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_0555 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_0555") 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_0555") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0555") - Notebooks
- Google Colab
- Kaggle
Model-J: SupViT Model (model_idx_0555)
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 | test |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 555 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9999 |
| Val Accuracy | 0.9211 |
| Test Accuracy | 0.9250 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chair, aquarium_fish, bridge, orange, television, poppy, butterfly, snail, kangaroo, rabbit, tulip, tractor, cup, lion, orchid, girl, turtle, willow_tree, sea, worm, plain, dinosaur, porcupine, train, rose, wardrobe, ray, telephone, lobster, mouse, pear, castle, dolphin, squirrel, boy, bee, bus, table, hamster, trout, rocket, bicycle, pickup_truck, mountain, cattle, clock, beaver, plate, shrew, possum
- Downloads last month
- 1
Model tree for ProbeX/Model-J__SupViT__model_idx_0555
Base model
google/vit-base-patch16-224