Instructions to use ProbeX/Model-J__MAE__model_idx_0136 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_0136 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_0136") 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_0136") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0136") - Notebooks
- Google Colab
- Kaggle
Model-J: MAE Model (model_idx_0136)
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 | 0.0005 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 136 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.4229 |
| Val Accuracy | 0.3656 |
| Test Accuracy | 0.3754 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
mushroom, seal, television, sunflower, orchid, skunk, snail, lamp, otter, snake, maple_tree, clock, castle, couch, beetle, aquarium_fish, motorcycle, skyscraper, shark, road, shrew, flatfish, wardrobe, cockroach, bowl, rose, pine_tree, camel, butterfly, lobster, lizard, bicycle, possum, orange, turtle, rabbit, palm_tree, raccoon, mouse, pear, table, plain, bridge, apple, worm, streetcar, bear, bottle, tulip, hamster
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Model tree for ProbeX/Model-J__MAE__model_idx_0136
Base model
facebook/vit-mae-base