Update README.md

README.md

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 ## For use with a Swift app like [**MOCHI DIFFUSION**](https://github.com/godly-devotion/MochiDiffusion) or the SwiftCLI
 
-The SD models in this repo are all "Original" and built for CPU and GPU.  They are each for the output size noted.  They are FP-16, with the standard SD-1.5 VAE embedded.  "Split-Einsum" versions that support ControlNet are currently being added.  Models that support both "Original" and "Split-Einsum" will be relocated to individual model repos listed on the [**CORE ML MODELS**](https://huggingface.co/coreml) main page.  The relocated models will also be linked below on this page.
-
-The Stable Diffusion v1.5 model and the other SD 1.5 type models contain both the standard Unet and the ControlledUnet used for a ControlNet pipeline.  The correct one will be used automatically based on whether a ControlNet is enabled or not.
-
-They have VAEEncoder.mlmodelc bundles that allow Image2Image to operate correctly at the noted resolutions, when used with a current Swift CLI pipeline or a current GUI built with ml-stable-diffusion 0.4.0 or ml-stable-diffusion 1.0.0, such as [**MOCHI DIFFUSION**](https://github.com/godly-devotion/MochiDiffusion) 3.2, 4.0, or later.
+All of the models in this repo work with Swift and the apple/ml-stable-diffusion pipeline (release 0.4.0 or 1.0.0).  They were not built for, and will not work with, a Python Diffusers pipeline.  They need [**ml-stable-diffusion**](https://github.com/apple/ml-stable-diffusion) for command line use, or a Swift app that supports ControlNet, such as the (June 2023) [**MOCHI DIFFUSION**](https://github.com/godly-devotion/MochiDiffusion) 4.0 version.
 
 The ControlNet models in this repo have both "Original" and "Split-Einsum" versions, all built for SD-1.5 type models.  They will not work with SD-2.1 type models.  The smaller zip files, with "SE", each have a single model for "Split-Einsum".  The larger zip files, without "SE", each have a set of "Original" models at 4 different resolutions. 
 
-All of the models in this repo work with Swift and the apple/ml-stable-diffusion pipeline (release 0.4.0 or 1.0.0).  They were not built for, and will not work with, a Python Diffusers pipeline.  They need [**ml-stable-diffusion**](https://github.com/apple/ml-stable-diffusion) for command line use, or a Swift app that supports ControlNet, such as the (June 2023) [**MOCHI DIFFUSION**](https://github.com/godly-devotion/MochiDiffusion) 4.0 version.
+The ControlNet model files are in the "CN" folder of this repo.  They are zipped and need to be unzipped after downloading.  The larger zips hold "Original" types at 512x512, 512x768, 768x512 and 768x768.  The smaller zips with "SE" have a single model for "Split-Einsum".
 
-The full SD type (base) models remaining at this repo are in the "SD" folder of this repo.  They are in subfolders by model name and individually zipped for a particular resolution.  They need to be unzipped for use after downloading.  The models still stored here are built only for "Original". 
+If you are using a GUI like [**MOCHI DIFFUSION**](https://github.com/godly-devotion/MochiDiffusion)  4.0, the app will most likely guide you to the correct location/arrangement for your ConrolNet model folder.
 
-The ControlNet model files are in the "CN" folder of this repo.  They are zipped and need to be unzipped after downloading.  The larger zips hold "Original" types at 512x512, 512x768, 768x512 and 768x768.  The smaller zips with "SE" have a single model for "Split-Einsum".
+Please note that when you unzip the "Originl" ControlNet files (for example Canny.zip) from this repo, they will unzip into a folder, with the actual four model files inside that folder.  This folder is just a holding folder for the zipping process.  **What you want to move into your ControlNet model folder in Mochi Diffusion will be the individual files, not the folder they unzip into.**  The "Split-Einsum" zips just have a single file and don't use a holding folder.  To make things even more confusing, on some Mac systems, an individual ControlNet model file, for example Canny-5x5.mlmodelc, will appear in Finder as a folder, not a file.  You want to move the Canny-5x5.mlmodelc file or folder (and other .mlmodelc files or folders) into your ControlNet store folder.  Don't move the plain "Canny" folder.  This is different from base models, where you do want to be moving the folder that the downloaded zip file unzips into.  See the images [**here**](https://huggingface.co/jrrjrr/CoreML-Models-For-ControlNet/blob/main/CN/-Settings.jpg) and [**here**](https://huggingface.co/jrrjrr/CoreML-Models-For-ControlNet/blob/main/CN/-Folders.jpg) for an example of how my folders are set up for Mochi Diffusion.
 
-There is also a "MISC" folder that has text files with some notes and a screencap of my directory structure.  These are provided for those who want to convert models themselves and/or run the models with a SwiftCLI.  The notes are not perfect, and may be out of date if any of the Python or CoreML packages referenced have been updated recently.  You can open a Discussion here if you need help with any of the "MISC" items. 
+The SD models in this repo are all "Original" and built for CPU and GPU.  They are each for the output size noted.  They are FP-16, with the standard SD-1.5 VAE embedded.  "Split-Einsum" versions that support ControlNet are currently being added.  Models that support both "Original" and "Split-Einsum" will be relocated to individual model repos listed on the [**CORE ML MODELS**](https://huggingface.co/coreml) main page.  The relocated models will also be linked below on this page.
 
-For command line use, the "MISC" notes cover setting up a miniconda3 environment.  If you are using the command line, please read the notes concerning naming and placement of your ControlNet model folder.  Briefly, they will need to go inside a "controlnet" folder that you placed inside your base model folder.  You'll need a "controlnet" folder inside each base model folder, or a symlink named "controlnet" pointing to a central folder with all your ControlNet models inside it.
+The full SD type (base) models remaining at this repo are in the "SD" folder of this repo.  They are in subfolders by model name and individually zipped for a particular resolution.  They need to be unzipped for use after downloading.  The models still stored here are built only for "Original". 
 
-If you are using a GUI like [**MOCHI DIFFUSION**](https://github.com/godly-devotion/MochiDiffusion)  4.0, the app will most likely guide you to the correct location/arrangement for your ConrolNet model folder.
+The Stable Diffusion v1.5 model and the other SD 1.5 type models contain both the standard Unet and the ControlledUnet used for a ControlNet pipeline.  The correct one will be used automatically based on whether a ControlNet is enabled or not.
 
-Please note that when you unzip the "Originl" ControlNet files (for example Canny.zip) from this repo, they will unzip into a folder, with the actual four model files inside that folder.  This folder is just a holding folder for the zipping process.  **What you want to move into your ControlNet model folder in Mochi Diffusion will be the individual files, not the folder they unzip into.**  The "Split-Einsum" zips just have a single file and don't use a holding folder.  To make things even more confusing, on some Mac systems, an individual ControlNet model file, for example Canny-5x5.mlmodelc, will appear in Finder as a folder, not a file.  You want to move the Canny-5x5.mlmodelc file or folder (and other .mlmodelc files or folders) into your ControlNet store folder.  Don't move the plain "Canny" folder.  This is different from base models, where you do want to be moving the folder that the downloaded zip file unzips into.  See the images [**here**](https://huggingface.co/jrrjrr/CoreML-Models-For-ControlNet/blob/main/CN/-Settings.jpg) and [**here**](https://huggingface.co/jrrjrr/CoreML-Models-For-ControlNet/blob/main/CN/-Folders.jpg) for an example of how my folders are set up for Mochi Diffusion.
+They have VAEEncoder.mlmodelc bundles that allow Image2Image to operate correctly at the noted resolutions, when used with a current Swift CLI pipeline or a current GUI built with ml-stable-diffusion 0.4.0 or ml-stable-diffusion 1.0.0, such as [**MOCHI DIFFUSION**](https://github.com/godly-devotion/MochiDiffusion) 3.2, 4.0, or later.
 
 The sizes noted for all model type inputs/outputs are WIDTH x HEIGHT.  A 512x768 is "portrait" orientation and a 768x512 is "landscape" orientation.
 
+There is also a "MISC" folder that has text files with some notes and a screencap of my directory structure.  These are provided for those who want to convert models themselves and/or run the models with a SwiftCLI.  The notes are not perfect, and may be out of date if any of the Python or CoreML packages referenced have been updated recently.  You can open a Discussion here if you need help with any of the "MISC" items. 
+
+For command line use, the "MISC" notes cover setting up a miniconda3 environment.  If you are using the command line, please read the notes concerning naming and placement of your ControlNet model folder.  Briefly, they will need to go inside a "controlnet" folder that you placed inside your base model folder.  You'll need a "controlnet" folder inside each base model folder, or a symlink named "controlnet" pointing to a central folder with all your ControlNet models inside it.
+
 **If you encounter any models that do not work correctly with image2image and/or a ControlNet, using the current apple/ml-stable-diffusion SwiftCLI pipeline for i2i or CN, or Mochi Diffusion 3.2 using i2i, or Mochi Diffusion 4.0 using i2i or CN, please leave a report in the Community Discussion area.  If you would like to add models that you have converted, leave a message there as well, and we will grant you access to this repo.**
- 
-## Base Models - A Variety Of SD-1.5-Type Models For Use With ControlNet
-Each folder remaining at this repo contains 4 "Origina" zipped model files, output sizes as indicated: 512x512, 512x768, 768x512 or 768x768
-- DreamShaper v5.0, 1.5-type model, "Original" & "Split-Einsum"  --  Reloacted to:  https://huggingface.co/coreml/coreml-DreamShaper-v5.0_cn
-- GhostMix v1.1, 1.5-type anime model, "Original" & "Split-Einsum"  --  Relocated to:  https://huggingface.co/coreml/coreml-ghostmix-v20-bakedVAE_cn
-- Realistic Vision v2.0, 1.5-type model, "Original" & "Split-Einsum"  --  Relocated to:  https://huggingface.co/coreml/coreml-realisticVision-v20_cn
-- MeinaMix v9.0 1.5-type anime model, "Original"
-- MyMerge v1.0 1.5-type NSFW model, "Original"
-- Stable Diffusion v1.5, "Original"
 
 ## ControlNet Models - All Current SD-1.5-Type ControlNet Models
 Each larger zip file contains a set of 4 "Original" types at resolutions of 512x512, 512x768, 768x512 and 768x768.  Each smaller zip file, with the "SE" notation, contains a single "Split-Einsum" file.
@@ -59,4 +50,13 @@ Each larger zip file contains a set of 4 "Original" types at resolutions of 512x
 - Segmentation  --  Find And Reuse Distinct Areas
 - Shuffle  --  Find And Reorder Major Elements 
 - SoftEdge  --  Find And Reuse Soft Edges
-- Tile  --  Subtle Variations Within Batch Run
+- Tile  --  Subtle Variations Within Batch Run
+
+## Base Models - A Variety Of SD-1.5-Type Models For Use With ControlNet
+Each folder remaining at this repo contains 4 "Origina" zipped model files, output sizes as indicated: 512x512, 512x768, 768x512 or 768x768
+- DreamShaper v5.0, 1.5-type model, "Original" & "Split-Einsum"  --  Reloacted to:  https://huggingface.co/coreml/coreml-DreamShaper-v5.0_cn
+- GhostMix v1.1, 1.5-type anime model, "Original" & "Split-Einsum"  --  Relocated to:  https://huggingface.co/coreml/coreml-ghostmix-v20-bakedVAE_cn
+- Realistic Vision v2.0, 1.5-type model, "Original" & "Split-Einsum"  --  Relocated to:  https://huggingface.co/coreml/coreml-realisticVision-v20_cn
+- MeinaMix v9.0 1.5-type anime model, "Original" & "Split-Einsum"  --  Relocated to:  https://huggingface.co/coreml/coreml-MeinaMix-v9_cn
+- MyMerge v1.0 1.5-type NSFW model, "Original"
+- Stable Diffusion v1.5, "Original"