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--- |
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license: mit |
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pipeline_tag: text-to-image |
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tags: |
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- onnx |
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- text-to-image |
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inference: false |
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--- |
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## Model Descriptions: |
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This repo contains ONNX model files for [madebyollin's Tiny AutoEncoder for Stable Diffusion](https://huggingface.co/madebyollin/taesd). |
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## Using in 🧨 diffusers |
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To install the requirements for this demo, do pip install optimum["onnxruntime"]. |
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```python |
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from optimum.onnxruntime import ORTStableDiffusionPipeline |
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model_id = "CompVis/stable-diffusion-v1-4" |
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pipeline = ORTStableDiffusionPipeline.from_pretrained(model_id, revision="onnx") |
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# Inject TAESD |
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taesd_id = "deinferno/taesd-onnx" |
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pipeline.vae_decoder = OnnxRuntimeModel.from_pretrained(taesd_id, subfolder = "vae_decoder") |
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pipeline.vae_encoder = OnnxRuntimeModel.from_pretrained(taesd_id, subfolder = "vae_encoder") |
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prompt = "sailing ship in storm by Leonardo da Vinci" |
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image = pipeline(prompt).images[0] |
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output.save("result.png") |
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``` |
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