Instructions to use ProbeX/Model-J__DINO__model_idx_0147 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_0147 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_0147") 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_0147") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0147") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0147")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0147")Model-J: DINO Model (model_idx_0147)
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 | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 147 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9776 |
| Val Accuracy | 0.8464 |
| Test Accuracy | 0.8480 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, fox, orange, cup, boy, porcupine, dolphin, lamp, skunk, beetle, telephone, aquarium_fish, train, pine_tree, bowl, orchid, lobster, shrew, oak_tree, mouse, turtle, willow_tree, tiger, mushroom, trout, kangaroo, castle, cloud, possum, girl, squirrel, whale, wardrobe, bottle, maple_tree, hamster, butterfly, lion, tank, snake, pickup_truck, crab, plate, motorcycle, beaver, tractor, sunflower, table, man, woman
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Model tree for ProbeX/Model-J__DINO__model_idx_0147
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_0147") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")