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Update app.py
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app.py
CHANGED
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@@ -41,7 +41,7 @@ def run_xlc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pag
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seed = random.randint(0, 9007199254740991)
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generator = torch.Generator(device="cuda").manual_seed(seed)
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image = pipe_xlc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25).images[0]
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return image, seed
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@@ -51,7 +51,7 @@ def run_xlnc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pa
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seed = random.randint(0, 9007199254740991)
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generator = torch.Generator(device="cuda").manual_seed(seed)
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image = pipe_xlnc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25).images[0]
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return image, seed
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seed = random.randint(0, 9007199254740991)
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generator = torch.Generator(device="cuda").manual_seed(seed)
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image = pipe_xlc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25, width=512, height=512).images[0]
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return image, seed
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seed = random.randint(0, 9007199254740991)
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generator = torch.Generator(device="cuda").manual_seed(seed)
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image = pipe_xlnc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25, width=512, height=512).images[0]
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return image, seed
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