Instructions to use ProbeX/Model-J__DINO__model_idx_0678 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_0678 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_0678") 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_0678") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0678") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0678")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0678")Model-J: DINO Model (model_idx_0678)
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 | 9e-05 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 678 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9998 |
| Val Accuracy | 0.9165 |
| Test Accuracy | 0.9224 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
sea, dolphin, mountain, snail, dinosaur, wardrobe, lion, caterpillar, beetle, wolf, couch, cup, lawn_mower, fox, bee, flatfish, table, rocket, poppy, skunk, elephant, bicycle, house, tiger, boy, bridge, bed, orange, porcupine, plain, turtle, spider, cloud, forest, butterfly, can, lamp, keyboard, rabbit, lizard, cockroach, trout, oak_tree, girl, road, shrew, tank, baby, clock, leopard
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Model tree for ProbeX/Model-J__DINO__model_idx_0678
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_0678") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")