Instructions to use ProbeX/Model-J__DINO__model_idx_0808 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_0808 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_0808") 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_0808") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0808") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0808")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0808")Model-J: DINO Model (model_idx_0808)
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 | val |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 808 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9714 |
| Val Accuracy | 0.8333 |
| Test Accuracy | 0.8390 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, bee, boy, lamp, baby, elephant, bus, otter, lobster, couch, cloud, wolf, lizard, fox, rose, telephone, can, shrew, sea, snake, lion, train, pickup_truck, crab, man, rabbit, flatfish, woman, sweet_pepper, mushroom, house, worm, pear, plain, clock, skyscraper, cattle, television, snail, mouse, dinosaur, seal, bear, plate, beetle, raccoon, squirrel, trout, aquarium_fish, orchid
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Model tree for ProbeX/Model-J__DINO__model_idx_0808
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_0808") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")