Model-J SupViT
Collection
998 items • Updated
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0487")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0487")Quick Links
Model-J: SupViT Model (model_idx_0487)
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
🌐 Project | 📃 Paper | 💻 GitHub | 🤗 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 | 7e-05 |
| LR Scheduler | cosine |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 487 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9998 |
| Val Accuracy | 0.9387 |
| Test Accuracy | 0.9496 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chimpanzee, girl, lawn_mower, forest, tiger, whale, house, train, poppy, crocodile, bridge, skyscraper, trout, spider, man, lizard, pickup_truck, sunflower, turtle, dinosaur, castle, tank, camel, seal, streetcar, rose, bowl, chair, flatfish, plate, bee, lion, lobster, kangaroo, table, worm, sea, tractor, cloud, plain, orange, oak_tree, couch, clock, mushroom, aquarium_fish, otter, rabbit, dolphin, maple_tree
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Model tree for ProbeX/Model-J__SupViT__model_idx_0487
Base model
google/vit-base-patch16-224
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0487") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")