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_0722")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0722")Quick Links
Model-J: SupViT Model (model_idx_0722)
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 | 3e-05 |
| LR Scheduler | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 722 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9967 |
| Val Accuracy | 0.9309 |
| Test Accuracy | 0.9318 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
sea, cattle, porcupine, squirrel, lawn_mower, whale, lizard, clock, shark, bus, caterpillar, tulip, bicycle, man, camel, kangaroo, boy, bear, streetcar, ray, leopard, trout, poppy, maple_tree, baby, shrew, lobster, possum, girl, table, apple, rabbit, skyscraper, mouse, bottle, snake, orchid, bed, willow_tree, crab, spider, tank, beaver, sunflower, can, keyboard, bridge, beetle, mountain, cockroach
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Model tree for ProbeX/Model-J__SupViT__model_idx_0722
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_0722") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")