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OnnxStack.Converter/README.md

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## Usage
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```bash
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convert.py --optimize --model_input '..\stable-diffusion-v1-5' --model_output '..\converted' --controlnet
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python convert.py --model_input '..\stable-diffusion-v1-5' --controlnet
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```
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`--optimize` - Run the model optimization
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`--model_input` - Safetensor model to convert
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`--model_output` - Output for converted ONNX model (NOTE: This folder is deleted before each run)
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`--model_output` - Output for converted ONNX model
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`--clean` - Clear convert/optimize model cache
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`--tempDir` - Directory for temp Olive files
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`--only_unet` - Only convert UNET model
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`--controlnet` - Create a ControlNet enabled Unet model

OnnxStack.Converter/latent_consistency/README.md

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## Usage
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```bash
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convert.py --model_input "D:\Models\LCM_Dreamshaper_v7" --controlnet
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python convert.py --model_input "D:\Models\LCM_Dreamshaper_v7" --controlnet
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```
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`--model_input` - Safetensor model to convert
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`--model_output` - Output for converted ONNX model
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`--controlnet` - Create a ControlNet enabled Unet model
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`--clean` - Clear convert/optimize model cache
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`--tempDir` - Directory for temp Olive files
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`--tempDir` - Directory for temp Olive files
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`--only_unet` - Only convert UNET model
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`--controlnet` - Create a ControlNet enabled Unet model

OnnxStack.Converter/stable_cascade/README.md

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## Usage
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```bash
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convert.py --optimize --model_input '..\stable-cascade' --image_encoder
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python convert.py --model_input "D:\Models\stable-cascade" --image_encoder
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```
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`--optimize` - Run the model optimization
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`--model_input` - Safetensor model to convert
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`--model_output` - Output for converted ONNX model (NOTE: This folder is deleted before each run)
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`--model_output` - Output for converted ONNX model
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`--clean` - Clear convert/optimize model cache
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`--tempDir` - Directory for temp Olive files
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`--only_unet` - Only convert UNET model
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`--image_encoder` - Convert the optional image encoder

OnnxStack.Converter/stable_diffusion/README.md

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## Usage
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```bash
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convert.py --model_input "D:\Models\stable-diffusion-v1-5" --controlnet
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python convert.py --model_input "D:\Models\stable-diffusion-v1-5" --controlnet
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```
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`--model_input` - Safetensor model to convert
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`--model_output` - Output for converted ONNX model
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`--controlnet` - Create a ControlNet enabled Unet model
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`--clean` - Clear convert/optimize model cache
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`--tempDir` - Directory for temp Olive files
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`--tempDir` - Directory for temp Olive files
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`--only_unet` - Only convert UNET model
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`--controlnet` - Create a ControlNet enabled Unet model

OnnxStack.Converter/stable_diffusion_xl/README.md

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`--model_output` - Output for converted ONNX model
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`--controlnet` - Create a ControlNet enabled Unet model
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`--clean` - Clear convert/optimize model cache
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`--tempDir` - Directory for temp Olive files
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`--only_unet` - Only convert UNET model
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`--controlnet` - Create a ControlNet enabled Unet model
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## Extra Requirements
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To successfully optimize SDXL models you will need the patched `vae` from repository below otherwise you may get black image results
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