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README.md
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```python
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# !pip install diffusers
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from diffusers import DiffusionPipeline
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import PIL.Image
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import numpy as np
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model_id = "fusing/glide-base"
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# load model and scheduler
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# run
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# process image to PIL
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image_pil = PIL.Image.fromarray(image_processed[0])
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# save image
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image_pil.save("test.png")
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## Samples
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1. 
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```python
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# !pip install diffusers
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import torch
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from diffusers import DiffusionPipeline
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import PIL.Image
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model_id = "fusing/glide-base"
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# load model and scheduler
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pipeline = DiffusionPipeline.from_pretrained(model_id)
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# run inference (text-conditioned denoising + upscaling)
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img = pipeline("a corgi wearing a red bowtie and a purple party hat")
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# process image to PIL
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img = img.squeeze(0)
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img = ((img + 1)*127.5).round().clamp(0, 255).to(torch.uint8).cpu().numpy()
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image_pil = PIL.Image.fromarray(img)
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# save image
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image_pil.save("test.png")
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## Samples
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1. 
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2. 
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3. 
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