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@@ -3,9 +3,9 @@ license: creativeml-openrail-m
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  # Just a repo for sharing random CoreML & Stable Diffusion files & info.<br><br>
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- Sept 26,2023:
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- I just created a fresh miniconda environment for model conversions.
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  It is working for SD-1.5 type models, including the ControlledUnet, both original and split-einsum-v1.
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@@ -15,14 +15,14 @@ I have not tried it with split-einsum-v2, or SDXL.
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  It uses mostly the current versions of available packages, specifically:
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- - macOS 14.0
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  - python==3.9
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  - coremltools==7.0
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- - diffusers==0.21.2
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- - python-coreml-stable-diffusion (pip -e . from a current git clone of ml-stable-diffusion)
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  - safetensors==0.3.3
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  - scikit-learn==1.1.2
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- - torch==2.0.0
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  - torch2coreml.py from the current diffusers main repo
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- The converted models work in both the standard Mochi Diffusion 4.2 and a version I built with Xcode 15 for macOS 14 using a git clone of the current Mochi Diffusion main branch.
 
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  # Just a repo for sharing random CoreML & Stable Diffusion files & info.<br><br>
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+ October 04, 2023:
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+ This is my current miniconda environment for model conversions.
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  It is working for SD-1.5 type models, including the ControlledUnet, both original and split-einsum-v1.
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  It uses mostly the current versions of available packages, specifically:
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+ - macOS 14.1
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  - python==3.9
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  - coremltools==7.0
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+ - diffusers==0.21.4
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+ - python-coreml-stable-diffusion (pip -e . from a current git clone of ml-stable-diffusio 1.1+)
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  - safetensors==0.3.3
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  - scikit-learn==1.1.2
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+ - torch==2.0.0 - - - (torch--2.0.1 also seems ok)
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  - torch2coreml.py from the current diffusers main repo
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+ The converted models work in both the standard Mochi Diffusion 4.2 and 4.3 and a version I built with Xcode 15 for macOS 14 using a git clone of the current Mochi Diffusion main branch.