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on
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Running
on
T4
Update app.py
Browse files
app.py
CHANGED
@@ -9,12 +9,11 @@ from huggingface_hub import hf_hub_download
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device = 'cuda' if torch.cuda.is_available() else 'cpu'
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torch.cuda.max_memory_allocated(device=device)
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torch.cuda.empty_cache()
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pipe = DiffusionPipeline.from_pretrained("circulus/canvers-fusionXL-v1", torch_dtype=torch.float16).to(device)
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pipe.enable_xformers_memory_efficient_attention()
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torch.cuda.empty_cache()
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def genie (Prompt, negative_prompt, height, width, scale, steps, seed):
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pipe=
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generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
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int_image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, output_type="latent").images
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torch.cuda.empty_cache()
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device = 'cuda' if torch.cuda.is_available() else 'cpu'
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torch.cuda.max_memory_allocated(device=device)
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torch.cuda.empty_cache()
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def genie (Prompt, negative_prompt, height, width, scale, steps, seed):
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pipe = DiffusionPipeline.from_pretrained("circulus/canvers-fusionXL-v1", torch_dtype=torch.float16).to(device)
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pipe.enable_xformers_memory_efficient_attention()
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torch.cuda.empty_cache()
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generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
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int_image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, output_type="latent").images
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torch.cuda.empty_cache()
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