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  1. README.md +16 -8
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@@ -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
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- The models were converted using the following flags:\
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- `--convert-vae-decoder --convert-vae-encoder --convert-unet --convert-text-encoder --bundle-resources-for-swift-cli --attention-implementation {SPLIT_EINSUM or ORIGINAL}`
 
 
 
 
 
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- ## Model version: `split_einsum` VS `original`
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- Depending on what compute unit you select, you will need to use the correct model version:
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- - `split_einsum` is compatible with all compute unit
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- - `original` is only compatible with CPU & GPU
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  ## Usage
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- Once the chosen model has been downloaded, simply unzip it to use it.
 
 
 
 
 
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+ ## Model Types
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+ Model files with `split_einsum` in the file name are compatible with all compute units.
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+ Model files with `original` in the file name are only compatible with CPU & GPU.
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+ Model files with a `no-i2i` suffix in the file name only work for Text2Image.
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+ Models with a `cn` suffix in the file name (or in their repo name) will work for Text2Image, Image2Image and ControlNet.
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+ Model files with neither a `no-i2i` nor a `cn` suffix in the file name will work for Text2Image and Image2Image.
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+ 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.
 
 
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  ## Usage
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+ Once the chosen model has been downloaded, simply unzip it and put it in your model folder to use it.
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+ ## Conversion Flags
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+ The models were converted using the following flags:\
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+ `--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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