Instructions to use ProbeX/Model-J__MAE__model_idx_0782 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_0782 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_0782") 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_0782") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0782") - Notebooks
- Google Colab
- Kaggle
Model-J: MAE Model (model_idx_0782)
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 | 0.0003 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 782 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9883 |
| Val Accuracy | 0.8704 |
| Test Accuracy | 0.8676 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
dolphin, tank, wolf, maple_tree, poppy, plain, house, rose, wardrobe, bowl, skyscraper, bee, dinosaur, cloud, orange, snake, forest, girl, road, man, seal, train, mountain, sunflower, tractor, table, couch, cup, lobster, leopard, apple, rabbit, fox, clock, lamp, rocket, otter, chair, sweet_pepper, bridge, possum, squirrel, mouse, cockroach, motorcycle, worm, snail, oak_tree, tiger, beaver
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Model tree for ProbeX/Model-J__MAE__model_idx_0782
Base model
facebook/vit-mae-base