Instructions to use ProbeX/Model-J__MAE__model_idx_0668 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__MAE__model_idx_0668 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__MAE__model_idx_0668") 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__MAE__model_idx_0668") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0668") - Notebooks
- Google Colab
- Kaggle
Model-J: MAE Model (model_idx_0668)
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 | MAE |
| Split | train |
| Base Model | facebook/vit-mae-base |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 668 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9985 |
| Val Accuracy | 0.8864 |
| Test Accuracy | 0.8856 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lizard, sea, rocket, bowl, bridge, girl, pear, raccoon, beaver, streetcar, shrew, bear, shark, bed, tank, television, possum, keyboard, rose, table, butterfly, house, trout, porcupine, whale, aquarium_fish, snail, plate, bee, lion, skunk, turtle, lamp, hamster, crab, mountain, palm_tree, kangaroo, telephone, baby, maple_tree, dinosaur, tulip, cup, train, motorcycle, sweet_pepper, otter, oak_tree, apple
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Model tree for ProbeX/Model-J__MAE__model_idx_0668
Base model
facebook/vit-mae-base