Instructions to use ProbeX/Model-J__DINO__model_idx_0695 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_0695 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_0695") 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_0695") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0695") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0695")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0695")Model-J: DINO Model (model_idx_0695)
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 | 5e-05 |
| LR Scheduler | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 695 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9994 |
| Val Accuracy | 0.9125 |
| Test Accuracy | 0.9130 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
butterfly, seal, sea, baby, fox, trout, maple_tree, wolf, beetle, spider, beaver, orchid, chimpanzee, woman, pear, poppy, flatfish, possum, lion, leopard, porcupine, house, couch, kangaroo, camel, tulip, raccoon, willow_tree, apple, orange, bee, rabbit, streetcar, plate, bed, motorcycle, squirrel, mushroom, bus, crocodile, bear, lamp, shrew, pine_tree, telephone, clock, chair, castle, cloud, boy
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Model tree for ProbeX/Model-J__DINO__model_idx_0695
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_0695") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")