Update README.md

README.md

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 This repository contains the dataset of model weights and utility files for [Interpreting the Weight Space of Customized Diffusion Models](https://snap-research.github.io/weights2weights/) (aka *weights2weights*). The code can be found at https://github.com/snap-research/weights2weights.
 
 # Files for creating *weights2weights* Space
-The `files/` folder contains the files needed for our code [here](https://snap-research.github.io/weights2weights/) in order to conduct sampling, inversion, and editing in *weights2weights* space.
-
-**Spatially Aligned Control**
-- `readout_sdxl_spatial_pose.pt` 
-- `readout_sdv15_spatial_pose.pt`
-    - Readout head trained with [OpenPose](https://arxiv.org/abs/1812.08008) pose skeletons as supervision on [PascalVOC](http://host.robots.ox.ac.uk/pascal/VOC) images, filtered only to those containing people.
-- `readout_sdxl_spatial_depth.pt`
-- `readout_sdv15_spatial_depth.pt`
-    - Readout head trained with [MiDaS](https://arxiv.org/abs/1907.01341) depth maps as supervision on [PascalVOC](http://host.robots.ox.ac.uk/pascal/VOC) images.
-- `readout_sdxl_spatial_edge.pt`
-- `readout_sdv15_spatial_edge.pt`
-    - Readout head trained with [HED](https://arxiv.org/abs/1504.06375) edge detections as supervision on [PascalVOC](http://host.robots.ox.ac.uk/pascal/VOC) images.
-
+The `files/` folder contains the files needed in our code [here](https://snap-research.github.io/weights2weights/) in order to conduct sampling, inversion, and editing in *weights2weights* space.
+- `files/V.pt`
+  - 99648x10000 dimensional tensor used to project or unproject LoRA weights onto a principal component representation in *w2w* space or to unproject back into the LoRA space.
+- 'files/mean.pt'
+  - 99648 dimensional tensor of the mean for each parameter in the original LoRA space. Used for projection/unprojection. 
+- 'files/std.pt'
+  - 99648 dimensional tensor of the standard deviation for each parameter in the original LoRA space. Used for projection/unprojection.
+- 'files/proj_1000pc.pt'
+  - 64974x1000 dimensional tensor where each row is a 1000-dimensional principal component projection for each identity-encoding model in our dataset of model weights.
+- 'files/pinverse.pt'
+  - Precomputed pseudoinverse of 'proj.pt', used for obtaining the classifier weight space directions given labels.
+- 'files/identity_df.pt'
+  - A pandas dataframe with each identity model in our dataset of weights and their associated binary labels. Used for getting labels for training linear classifiers. 
+- 'files/weight_dimensions.pt'
+  - A dictionary of the dimensionality for each LoRA module in the diffusion UNet. Used to save models in Diffusers pipeline format. 
 
 **Drag-Based Manipulation**
 - `readout_sdxl_drag_correspondence.pt`