Update README.md

README.md

@@ -15,7 +15,7 @@ The Stable Diffusion v1.5 model and the other SD 1.5 type models contain both th
 
 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, such as Mochi Diffusion 3.2 or later.
 
-All of the ControlNet models are also "original" ones, built for CPU and GPU compute units (cpuAndGPU) and for SD-1.5 type models.  The zip files each contain have a set of models at 4 resolutions.  They may also work with split-einsum models, using CPU and GPU (not CPU and NE), but they will not work with SD-2.1 type models at all.
+All of the ControlNet models are also "Original" ones, built for CPU and GPU compute units (cpuAndGPU) and for SD-1.5 type models.  The zip files each have a set of models at 4 resolutions.  They may also work with split-einsum models, using CPU and GPU (not CPU and NE), but they will not work with SD-2.1 type models at all.
 
 All of the models in this repo will only work with Swift and the current ml-stable-diffusion pipeline (0.4.0).  They were not built for a python diffusers pipeline.  They need apple/ml-stable-diffusion (from GitHub) for command line use or a Swift app that supports ControlNet, such as the Mochi Diffusion test version currently in a closed beta test at https://github.com/godly-devotion/MochiDiffusion that supports ControlNet.  Join the Mochi Difusion Discord server at https://discord.gg/x2kartzxGv to request access to the beta test version.