Instructions to use ProbeX/Model-J__DINO__model_idx_0880 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_0880 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_0880") 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_0880") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0880") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0880")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0880")Model-J: DINO Model (model_idx_0880)
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 | cosine_with_restarts |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 880 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9992 |
| Val Accuracy | 0.9432 |
| Test Accuracy | 0.9362 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
snake, orange, possum, pear, wardrobe, ray, apple, crab, mushroom, shark, television, train, keyboard, can, orchid, raccoon, bottle, dinosaur, skunk, motorcycle, poppy, telephone, lion, pickup_truck, lamp, bicycle, tiger, woman, camel, cup, lizard, snail, bus, mountain, aquarium_fish, plate, streetcar, plain, girl, squirrel, leopard, elephant, beetle, shrew, porcupine, worm, crocodile, rocket, hamster, house
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Model tree for ProbeX/Model-J__DINO__model_idx_0880
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_0880") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")