Instructions to use ProbeX/Model-J__DINO__model_idx_0243 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_0243 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_0243") 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_0243") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0243") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0243")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0243")Model-J: DINO Model (model_idx_0243)
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 | test |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 243 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9940 |
| Val Accuracy | 0.9168 |
| Test Accuracy | 0.9254 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
hamster, clock, leopard, skyscraper, bowl, television, orchid, forest, telephone, tiger, pickup_truck, skunk, lizard, motorcycle, bottle, lawn_mower, table, tractor, snake, baby, cockroach, tulip, worm, butterfly, boy, lobster, crab, beaver, spider, porcupine, bus, dinosaur, ray, train, cloud, cattle, turtle, girl, camel, road, rose, oak_tree, caterpillar, otter, squirrel, mushroom, seal, mountain, keyboard, chimpanzee
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Model tree for ProbeX/Model-J__DINO__model_idx_0243
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_0243") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")