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Update app.py
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app.py
CHANGED
@@ -107,9 +107,9 @@ def load_and_prepare_model(model_id):
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#pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",use_safetensors=True)
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pipe = StableDiffusionXLPipeline.from_pretrained(
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-
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#'John6666/pornworks-sexy-beauty-v04-sdxl',
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'John6666/uber-realistic-porn-merge-xl-urpmxl-v3-sdxl',
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#'ford442/Juggernaut-XI-v11-fp32',
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# 'SG161222/RealVisXL_V5.0',
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#torch_dtype=torch.bfloat16,
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@@ -510,14 +510,14 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
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minimum=0.1,
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maximum=30,
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step=0.1,
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value=
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)
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num_inference_steps = gr.Slider(
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label="Number of inference steps",
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minimum=10,
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maximum=1000,
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step=10,
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value=
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)
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gr.Examples(
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#pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",use_safetensors=True)
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pipe = StableDiffusionXLPipeline.from_pretrained(
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'ford442/RealVisXL_V5.0_BF16',
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#'John6666/pornworks-sexy-beauty-v04-sdxl',
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#'John6666/uber-realistic-porn-merge-xl-urpmxl-v3-sdxl',
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#'ford442/Juggernaut-XI-v11-fp32',
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# 'SG161222/RealVisXL_V5.0',
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#torch_dtype=torch.bfloat16,
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minimum=0.1,
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maximum=30,
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step=0.1,
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value=3.8,
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)
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num_inference_steps = gr.Slider(
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label="Number of inference steps",
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minimum=10,
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maximum=1000,
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step=10,
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value=170,
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)
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gr.Examples(
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