Update README.md

README.md

@@ -17,20 +17,28 @@ By organizing Core ML models in one place, it will be easier to find them and fo
 
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-## Conversion Flags
+## Model Types
 
-The models were converted using the following flags:\
-`--convert-vae-decoder --convert-vae-encoder --convert-unet --convert-text-encoder --bundle-resources-for-swift-cli --attention-implementation {SPLIT_EINSUM or ORIGINAL}`
+Model files with `split_einsum` in the file name are compatible with all compute units.
+
+Model files with `original` in the file name are only compatible with CPU & GPU.
+
+Model files with a `no-i2i` suffix in the file name only work for Text2Image.
+
+Models with a `cn` suffix in the file name (or in their repo name) will work for Text2Image, Image2Image and ControlNet.
 
-## Model version: `split_einsum` VS `original`
+Model files with neither a `no-i2i` nor a `cn` suffix in the file name will work for Text2Image and Image2Image.
 
-Depending on what compute unit you select, you will need to use the correct model version:
-- `split_einsum` is compatible with all compute unit
-- `original` is only compatible with CPU & GPU
+If you are using Mochi Diffusion v3.2, v4.0 or later versions, some model files with neither a `no-i2i` nor a `cn` suffix in the file name might need a simple modification to enable Image2Image to work correctly.  Please go [HERE](https://huggingface.co/jrrjrr/VAEEncoder_Set_For_Image2Image_With_Mochi_Diffusion_v3.2) for more information.
 
 ## Usage
 
-Once the chosen model has been downloaded, simply unzip it to use it.
+Once the chosen model has been downloaded, simply unzip it and put it in your model folder to use it.
+
+## Conversion Flags
+
+The models were converted using the following flags:\
+`--convert-vae-decoder --convert-vae-encoder --convert-unet --unet-support-controlnet --convert-text-encoder --bundle-resources-for-swift-cli --attention-implementation {SPLIT_EINSUM or ORIGINAL}`
 
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