Instructions to use ProbeX/Model-J__DINO__model_idx_0289 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__DINO__model_idx_0289 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0289") 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__DINO__model_idx_0289") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0289") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0289")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0289")Model-J: DINO Model (model_idx_0289)
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 | DINO |
| Split | train |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 3e-05 |
| LR Scheduler | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 289 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9998 |
| Val Accuracy | 0.9291 |
| Test Accuracy | 0.9316 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
dinosaur, skyscraper, cattle, worm, leopard, man, train, apple, raccoon, cloud, plate, spider, tank, shark, sunflower, willow_tree, squirrel, castle, elephant, flatfish, wolf, tractor, bed, dolphin, road, bicycle, poppy, rabbit, baby, woman, forest, shrew, crocodile, skunk, maple_tree, fox, plain, sweet_pepper, aquarium_fish, beaver, chair, bus, orange, whale, wardrobe, pear, girl, seal, chimpanzee, can
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Model tree for ProbeX/Model-J__DINO__model_idx_0289
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_0289") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")