Instructions to use ProbeX/Model-J__SupViT__model_idx_0674 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_0674 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_0674") 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_0674") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0674") - Notebooks
- Google Colab
- Kaggle
Model-J: SupViT Model (model_idx_0674)
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 | 7e-05 |
| LR Scheduler | cosine |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 674 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9997 |
| Val Accuracy | 0.9525 |
| Test Accuracy | 0.9604 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
trout, possum, forest, lobster, rose, leopard, whale, lawn_mower, cockroach, turtle, bridge, mountain, lamp, bowl, worm, skyscraper, beetle, lion, dolphin, bee, baby, orange, shark, bed, skunk, pear, butterfly, tank, girl, can, rocket, television, palm_tree, kangaroo, chimpanzee, mouse, sweet_pepper, snake, train, chair, plain, sunflower, seal, cattle, dinosaur, bus, fox, tulip, clock, sea
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Model tree for ProbeX/Model-J__SupViT__model_idx_0674
Base model
google/vit-base-patch16-224