Instructions to use ProbeX/Model-J__MAE__model_idx_0800 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_0800 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_0800") 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_0800") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0800") - Notebooks
- Google Colab
- Kaggle
Model-J: MAE Model (model_idx_0800)
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 | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 800 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.7418 |
| Val Accuracy | 0.7112 |
| Test Accuracy | 0.7130 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
train, clock, plate, boy, man, otter, chair, dinosaur, sea, keyboard, cloud, maple_tree, lamp, seal, pine_tree, forest, butterfly, hamster, road, dolphin, bottle, tractor, bee, sunflower, streetcar, table, possum, chimpanzee, beaver, porcupine, mountain, mushroom, girl, worm, whale, skyscraper, wardrobe, aquarium_fish, flatfish, fox, tiger, squirrel, rocket, bed, willow_tree, can, orange, bicycle, mouse, sweet_pepper
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Model tree for ProbeX/Model-J__MAE__model_idx_0800
Base model
facebook/vit-mae-base