Model-J DINO
Collection
1002 items • Updated
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0543")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0543")Quick Links
Model-J: DINO Model (model_idx_0543)
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 | DINO |
| Split | train |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | linear |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 543 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9998 |
| Val Accuracy | 0.9232 |
| Test Accuracy | 0.9254 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lizard, clock, mouse, woman, lawn_mower, mushroom, possum, bear, road, tractor, house, beaver, beetle, cockroach, tulip, television, maple_tree, lamp, forest, elephant, wolf, shrew, table, mountain, bus, ray, snail, seal, can, chimpanzee, skunk, sea, otter, rocket, spider, keyboard, sunflower, pickup_truck, camel, boy, cup, baby, motorcycle, telephone, train, raccoon, tank, poppy, dinosaur, caterpillar
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Model tree for ProbeX/Model-J__DINO__model_idx_0543
Base model
facebook/dino-vitb16
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0543") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")