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_0092")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0092")Quick Links
Model-J: DINO Model (model_idx_0092)
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 | val |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 92 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.3669 |
| Val Accuracy | 0.3421 |
| Test Accuracy | 0.3284 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lizard, woman, orange, ray, road, bottle, willow_tree, motorcycle, bridge, lobster, house, baby, sea, rocket, hamster, couch, butterfly, bicycle, flatfish, worm, skunk, clock, raccoon, orchid, plain, spider, can, elephant, castle, seal, bed, bear, pickup_truck, cattle, sweet_pepper, telephone, lawn_mower, possum, squirrel, tiger, leopard, tulip, chimpanzee, trout, cloud, oak_tree, maple_tree, snake, crocodile, snail
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Model tree for ProbeX/Model-J__DINO__model_idx_0092
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_0092") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")