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Update app.py
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app.py
CHANGED
@@ -16,8 +16,8 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
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dtype = torch.float16
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vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
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repo = "
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pipe =
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help_text = """
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To optimize image results:
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@@ -43,7 +43,7 @@ def set_timesteps_patched(self, num_inference_steps: int, device = None):
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self.sigmas = self.sigmas.to("cpu")
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# Image Editor
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edit_file = hf_hub_download(
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EDMEulerScheduler.set_timesteps = set_timesteps_patched
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pipe_edit = StableDiffusionXLInstructPix2PixPipeline.from_single_file(
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edit_file, num_in_channels=8, is_cosxl_edit=True, vae=vae, torch_dtype=torch.float16,
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dtype = torch.float16
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vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
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repo = "fluently/Fluently-XL-Final"
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pipe = StableDiffusionXLPipeline.from_pretrained(repo, torch_dtype=torch.float16, vae=vae).to(device)
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help_text = """
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To optimize image results:
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self.sigmas = self.sigmas.to("cpu")
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# Image Editor
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edit_file = hf_hub_download(repo, filename="cosxl_edit.safetensors")
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EDMEulerScheduler.set_timesteps = set_timesteps_patched
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pipe_edit = StableDiffusionXLInstructPix2PixPipeline.from_single_file(
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edit_file, num_in_channels=8, is_cosxl_edit=True, vae=vae, torch_dtype=torch.float16,
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