| library_name: peft | |
| pipeline_tag: text-to-image | |
| tags: | |
| - probex | |
| - model-j | |
| - weight-space-learning | |
| - lora | |
| - stable-diffusion | |
| # Model-J: SD_1k (Bundled LoRA Models) | |
| This repository contains **SD_1k** LoRA models from the **Model-J** dataset, introduced in: | |
| **Learning on Model Weights using Tree Experts** (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen | |
| <p align="center"> | |
| 🌐 <a href="https://horwitz.ai/probex" target="_blank">Project</a> | 📃 <a href="https://arxiv.org/abs/2410.13569" target="_blank">Paper</a> | 💻 <a href="https://github.com/eliahuhorwitz/ProbeX" target="_blank">GitHub</a> | 🤗 <a href="https://huggingface.co/ProbeX" target="_blank">Dataset</a> | |
| </p> | |
|  | |
| ## Overview | |
| This repository bundles all SD_1k LoRA models into a single repo. Each model is a LoRA adapter fine-tuned on images of a specific ImageNet class using Stable Diffusion. Each model directory also contains the training images used for fine-tuning. | |
| ## Repository Structure | |
| ``` | |
| {split}/model_idx_{XXXX}/ | |
| pytorch_lora_weights.safetensors | |
| training_images/ | |
| README.md | |
| ``` | |
| Splits: `train`, `val`, `test`, `val_holdout`, `test_holdout` | |
| For detailed hyperparameters of each model, see the README.md in each model's directory or the [Model-J dataset](https://huggingface.co/datasets/ProbeX/Model-J). | |