Update README.md

README.md

@@ -393,4 +393,68 @@ configs:
     path: SupViT/val-*
   - split: test
     path: SupViT/test-*
+tags:
+  - probex
+  - model-j
+  - weight-space-learning
+  - model-zoo
+  - hyperparameters
+  - stable-diffusion
+  - vit
+  - resnet
+size_categories:
+  - 10K<n<100K
 ---
+
+# Model-J Dataset
+
+This dataset contains the hyperparameters, metadata, and Hugging Face links for all models in 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">Models</a>
+</p>
+
+![ProbeX](https://raw.githubusercontent.com/eliahuhorwitz/ProbeX/main/imgs/poster.png)
+
+## Overview
+
+Model-J is a large-scale dataset of trained neural networks designed for research on learning from model weights. It contains **14,004** models spanning 6 subsets, each with train/val/test splits. Every row in this dataset provides the full training hyperparameters, performance metrics, and a direct link to the corresponding model weights on Hugging Face.
+
+## Subsets
+
+### Discriminative (one model per HF repo)
+
+| Subset | Base Model | Train | Val | Test | Total |
+|---|---|---|---|---|---|
+| **DINO** | `facebook/dino-vitb16` | 701 | 100 | 201 | 1,002 |
+| **MAE** | `facebook/vit-mae-base` | 701 | 100 | 201 | 1,002 |
+| **SupViT** | `google/vit-base-patch16-224` | 698 | 99 | 201 | 998 |
+| **ResNet** | `microsoft/resnet-18` | 701 | 100 | 201 | 1,002 |
+
+Each discriminative model is a full fine-tuned classifier hosted in its own Hugging Face repository. The `hf_model_id` and `hf_model_url` columns point directly to the model.
+
+### Generative (bundled LoRA models in a single HF repo)
+
+| Subset | Train | Val | Test | Val Holdout | Test Holdout | Total |
+|---|---|-----|------|-------------|--------------|---|
+| **SD_200** | 3,500 | 251 | 499  | 249 | 501          | 5,000        |
+| **SD_1k** | 3,500 | 251 | 499  | 249 | 501          | 5,000       |
+
+
+Each generative model is a LoRA adapter. All models within a subset are bundled into a single Hugging Face repository ([SD_1k](https://huggingface.co/ProbeX/Model-J__SD_1k), [SD_200](https://huggingface.co/ProbeX/Model-J__SD_200)). The `hf_model_path` column provides the path to each model's weights within the repo. Each model's directory also contains its training images.
+
+## Citation
+If you find this useful for your research, please use the following.
+
+```
+@InProceedings{Horwitz_2025_CVPR,
+    author    = {Horwitz, Eliahu and Cavia, Bar and Kahana, Jonathan and Hoshen, Yedid},
+    title     = {Learning on Model Weights using Tree Experts},
+    booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
+    month     = {June},
+    year      = {2025},
+    pages     = {20468-20478}
+}
+```