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--- |
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library_name: diffusers |
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tags: |
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- text-to-image |
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--- |
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```python |
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from diffusers import DiffusionPipeline |
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pipeline = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-sdxl-custom-all", trust_remote_code=True) |
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assert pipeline.config.unet == ('diffusers_modules.local.my_unet_model', 'MyUNetModel') |
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assert pipeline.config.scheduler == ('diffusers_modules.local.my_scheduler', 'MyScheduler') |
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assert pipeline.__class__.__name__ == "MyPipeline" |
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pipeline = pipeline.to(torch_device) |
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images = pipeline("test", num_inference_steps=2, output_type="np")[0] |
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assert images.shape == (1, 64, 64, 3) |
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``` |
