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# OnnxStack.Converter
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## Requirements
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```bash
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pip install onnxruntime-directml
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pip install olive-ai[directml]
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python -m pip install -r requirements.txt
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```
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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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```
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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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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' --model_output '..\converted'
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convert.py --optimize --model_input '..\stable-cascade' --image_encoder
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```
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`--optimize` - Run the model optimization
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# OnnxStack.Converter
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## Requirements
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```bash
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pip install onnxruntime-directml
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pip install olive-ai[directml]
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python -m pip install -r requirements.txt
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```
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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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```
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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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