Update README.md

README.md

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 # ControlNet v1.1 Models And Compatible Stable Diffusion v1.5 Type Models Converted To Apple CoreML Format
 
-## For use with a Swift app or the SwiftCLI
+## For use with a Swift app like  [MOCHI DIFFUSION](https://github.com/godly-devotion/MochiDiffusio) 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 fp16, with the standard SD-1.5 VAE embedded.  
 
@@ -17,7 +17,7 @@ They have VAEEncoder.mlmodelc bundles that allow Image2Image to operate correctl
 
 All of the ControlNet models in this repo are "Original" ones, built for CPU and GPU compute units (cpuAndGPU) and for SD-1.5 type models.  They will not work with SD-2.1 type models.  The zip files each have a set of models at 4 resolutions.  "Split-Einsum" versions for use with the Neural Engine (CPU and NE) are available at a different repo.  A link to that repo is at the bottom of this page. 
 
-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 new (June 2023) [**Mochi Diffusion**](https://github.com/godly-devotion/MochiDiffusion) 4.0 version.
+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 new (June 2023) [**MOCHI DIFFUSION#*](https://github.com/godly-devotion/MochiDiffusion) 4.0 version.
 
 The full SD models 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.
 
@@ -33,7 +33,7 @@ Please note that when you unzip the ControlNet files (for example Canny.zip) fro
 
 The sizes noted for all model type inputs/outputs are WIDTH x HEIGHT.  A 512x768 is "portrait" orientation and a 768x512 is "landscape" orientation.
 
-**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 I'll grant you access to this repo.**
+**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 contains 4 zipped model files, output sizes as indicated: 512x512, 512x768, 768x512 or 768x768