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Update app.py
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app.py
CHANGED
@@ -301,7 +301,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
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image = sdxl(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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if Model == '
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pipe = DiffusionPipeline.from_pretrained("circulus/canvers-fusionXL-v1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-real-v3.8.1")
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pipe.enable_xformers_memory_efficient_attention()
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@@ -342,11 +342,11 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
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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', 'Test'], 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,
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gr.Slider(512,
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gr.Slider(1, maximum=15, value=5, step=.25, label='Guidance Scale'),
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gr.Slider(25, maximum=100, value=50, step=25, 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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@@ -354,6 +354,6 @@ gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Anime', 'Disney', 'StoryB
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gr.Slider(minimum=.9, maximum=.99, value=.95, step=.01, label='Refiner Denoise Start %'),
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gr.Radio(["Yes", "No"], label = 'SD X2 Latent Upscaler?', value="No")],
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outputs=gr.Image(label='Generated Image'),
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title="Manju Dream Booth V1.
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description="<br><br><b/>Warning: This Demo is capable of producing NSFW content.",
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article = "If You Enjoyed this Demo and would like to Donate, you can send any amount to any of these Wallets. <br><br>SHIB (BEP20): 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>PayPal: https://www.paypal.me/ManjushriBodhisattva <br>ETH: 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>DOGE: D9QdVPtcU1EFH8jDC8jhU9uBcSTqUiA8h6<br><br>Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80)
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image = sdxl(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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if Model == 'FusionXL':
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pipe = DiffusionPipeline.from_pretrained("circulus/canvers-fusionXL-v1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-real-v3.8.1")
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pipe.enable_xformers_memory_efficient_attention()
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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','Test'], 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, 2048, 768, step=128, label='Height'),
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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(25, maximum=100, value=50, step=25, 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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gr.Slider(minimum=.9, maximum=.99, value=.95, step=.01, label='Refiner Denoise Start %'),
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gr.Radio(["Yes", "No"], label = 'SD X2 Latent Upscaler?', value="No")],
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outputs=gr.Image(label='Generated Image'),
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title="Manju Dream Booth V1.8 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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article = "If You Enjoyed this Demo and would like to Donate, you can send any amount to any of these Wallets. <br><br>SHIB (BEP20): 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>PayPal: https://www.paypal.me/ManjushriBodhisattva <br>ETH: 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>DOGE: D9QdVPtcU1EFH8jDC8jhU9uBcSTqUiA8h6<br><br>Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80)
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