Instructions to use ProbeX/Model-J__SupViT__model_idx_0676 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_0676 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_0676") 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_0676") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0676") - Notebooks
- Google Colab
- Kaggle
Model-J: SupViT Model (model_idx_0676)
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 | 0.009 |
| Seed | 676 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9996 |
| Val Accuracy | 0.9453 |
| Test Accuracy | 0.9496 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chair, pear, mouse, couch, bridge, road, bed, fox, cattle, flatfish, skunk, boy, mountain, porcupine, plain, mushroom, dolphin, orchid, motorcycle, cup, rabbit, clock, palm_tree, aquarium_fish, kangaroo, hamster, forest, chimpanzee, crocodile, girl, woman, cloud, train, leopard, tiger, cockroach, bus, lion, turtle, squirrel, can, bicycle, dinosaur, streetcar, sweet_pepper, beetle, lizard, wardrobe, house, pickup_truck
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Model tree for ProbeX/Model-J__SupViT__model_idx_0676
Base model
google/vit-base-patch16-224