Update app.py
Browse files
app.py
CHANGED
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@@ -7,7 +7,7 @@ from diffusers import DiffusionPipeline
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import torch
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_repo_id = "
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if torch.cuda.is_available():
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torch_dtype = torch.bfloat16
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@@ -28,8 +28,8 @@ def infer(
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randomize_seed=False,
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width=1024,
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height=1024,
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guidance_scale=
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num_inference_steps=
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progress=gr.Progress(track_tqdm=True),
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):
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if randomize_seed:
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@@ -119,7 +119,7 @@ with gr.Blocks(css=css) as demo:
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minimum=0.0,
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maximum=7.5,
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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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@@ -127,7 +127,7 @@ with gr.Blocks(css=css) as demo:
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minimum=1,
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maximum=50,
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step=1,
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value=
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)
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gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=infer, cache_examples=True, cache_mode="lazy")
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import torch
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_repo_id = "tensorart/stable-diffusion-3.5-large-TurboX"
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if torch.cuda.is_available():
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torch_dtype = torch.bfloat16
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randomize_seed=False,
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width=1024,
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height=1024,
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guidance_scale=1.5,
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num_inference_steps=8,
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progress=gr.Progress(track_tqdm=True),
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):
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if randomize_seed:
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minimum=0.0,
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maximum=7.5,
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step=0.1,
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value=1.5,
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)
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num_inference_steps = gr.Slider(
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minimum=1,
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maximum=50,
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step=1,
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value=8,
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)
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gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=infer, cache_examples=True, cache_mode="lazy")
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