---
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>

![ProbeX](https://raw.githubusercontent.com/eliahuhorwitz/ProbeX/main/imgs/poster.png)

## 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).