Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
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@@ -3,8 +3,10 @@ from diffusers import StableDiffusionXLPipeline, UNet2DConditionModel, EulerDisc
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import torch
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from huggingface_hub import hf_hub_download
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from safetensors.torch import load_file
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import spaces
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vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
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### SDXL Turbo ####
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@@ -33,6 +35,7 @@ pipe_lightning = StableDiffusionXLPipeline.from_pretrained(base,
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variant="fp16"
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)#.to("cuda")
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del unet
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pipe_lightning.scheduler = EulerDiscreteScheduler.from_config(pipe_lightning.scheduler.config, timestep_spacing="trailing", prediction_type="sample")
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#pipe_lightning.to("cuda")
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@@ -55,6 +58,7 @@ pipe_hyper = StableDiffusionXLPipeline.from_pretrained(base,
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pipe_hyper.scheduler = LCMScheduler.from_config(pipe_hyper.scheduler.config)
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#pipe_hyper.to("cuda")
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del unet
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@spaces.GPU
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def run_comparison(prompt):
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import torch
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from huggingface_hub import hf_hub_download
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from safetensors.torch import load_file
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import gc
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import spaces
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vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
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### SDXL Turbo ####
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variant="fp16"
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)#.to("cuda")
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del unet
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gc.collect()
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pipe_lightning.scheduler = EulerDiscreteScheduler.from_config(pipe_lightning.scheduler.config, timestep_spacing="trailing", prediction_type="sample")
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#pipe_lightning.to("cuda")
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pipe_hyper.scheduler = LCMScheduler.from_config(pipe_hyper.scheduler.config)
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#pipe_hyper.to("cuda")
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del unet
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gc.collect()
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@spaces.GPU
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def run_comparison(prompt):
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