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Running
on
T4
Running
on
T4
Update app.py
Browse files
app.py
CHANGED
@@ -349,10 +349,19 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
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image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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torch.cuda.empty_cache()
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return image
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return image
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gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Anime', 'Disney', 'StoryBook', 'SemiReal', 'Animagine XL 3.0', 'SDXL 1.0', 'FusionXL'], value='PhotoReal', label='Choose Model'),
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gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'),
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gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'),
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gr.Slider(512, 1024, 768, step=128, label='Height'),
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image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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torch.cuda.empty_cache()
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return image
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if Model == 'SDXL-Turbo':
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#from diffusers import AutoPipelineForText2Image
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#pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
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#pipe.to("cuda")
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torch.cuda.empty_cache()
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pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
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pipe.enable_xformers_memory_efficient_attention()
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pipe = pipe.to(device)
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image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
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return image
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gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Anime', 'Disney', 'StoryBook', 'SemiReal', 'Animagine XL 3.0', 'SDXL 1.0', 'FusionXL', 'SDXL-Turbo'], value='PhotoReal', label='Choose Model'),
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gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'),
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gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'),
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gr.Slider(512, 1024, 768, step=128, label='Height'),
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