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Running
on
A10G
Running
on
A10G
Update app.py
Browse files
app.py
CHANGED
@@ -14,7 +14,6 @@ pipe.enable_xformers_memory_efficient_attention()
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pipe = pipe.to(device)
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torch.cuda.empty_cache()
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-
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def genie (Prompt, negative_prompt, height, width, scale, steps, seed, upscale):
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generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
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torch.cuda.empty_cache()
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@@ -27,7 +26,7 @@ gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generat
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gr.Slider(512, 2048, 768, step=128, label='Width'),
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gr.Slider(1, maximum=15, value=5, step=.25, label='Guidance Scale'),
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gr.Slider(5, maximum=100, value=50, step=5, label='Number of Iterations'),
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gr.Slider(minimum=0, step=1, maximum=9999999999999999, randomize=True, label='Seed: 0 is Random')]
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outputs=gr.Image(label='Generated Image'),
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title="Manju Dream Booth V1.9 with SDXL 1.0 Refiner and SD X2 Latent Upscaler - GPU",
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description="<br><br><b/>Warning: This Demo is capable of producing NSFW content.",
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pipe = pipe.to(device)
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torch.cuda.empty_cache()
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def genie (Prompt, negative_prompt, height, width, scale, steps, seed, upscale):
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generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
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torch.cuda.empty_cache()
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gr.Slider(512, 2048, 768, step=128, label='Width'),
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gr.Slider(1, maximum=15, value=5, step=.25, label='Guidance Scale'),
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gr.Slider(5, maximum=100, value=50, step=5, label='Number of Iterations'),
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gr.Slider(minimum=0, step=1, maximum=9999999999999999, randomize=True, label='Seed: 0 is Random')],
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outputs=gr.Image(label='Generated Image'),
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title="Manju Dream Booth V1.9 with SDXL 1.0 Refiner and SD X2 Latent Upscaler - GPU",
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description="<br><br><b/>Warning: This Demo is capable of producing NSFW content.",
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