Instructions to use ProbeX/Model-J__DINO__model_idx_0305 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_0305 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_0305") 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_0305") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0305") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0305")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0305")Model-J: DINO Model (model_idx_0305)
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 | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 305 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9992 |
| Val Accuracy | 0.9248 |
| Test Accuracy | 0.9222 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
willow_tree, otter, tank, caterpillar, keyboard, elephant, man, possum, cup, bowl, lizard, leopard, train, poppy, orange, wardrobe, chimpanzee, forest, plate, butterfly, streetcar, pine_tree, wolf, beaver, skyscraper, woman, rabbit, trout, crab, orchid, clock, dolphin, baby, castle, cattle, sunflower, lobster, oak_tree, whale, crocodile, tiger, road, lamp, mountain, seal, ray, apple, flatfish, worm, cloud
- Downloads last month
- 4
Model tree for ProbeX/Model-J__DINO__model_idx_0305
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_0305") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")