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7d47252
Update app.py
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app.py
CHANGED
@@ -14,7 +14,7 @@ from diffusers import AutoPipelineForText2Image, DPMSolverMultistepScheduler
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from huggingface_hub import hf_hub_download
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DESCRIPTION = """
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# Res-Adapter
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**Demo by [ameer azam] - [Twitter](https://twitter.com/Ameerazam18) - [GitHub](https://github.com/AMEERAZAM08)) - [Hugging Face](https://huggingface.co/ameerazam08)**
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This is a demo of https://huggingface.co/jiaxiangc/res-adapter LORAs by ByteDance
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"""
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@@ -29,9 +29,10 @@ ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD") == "1"
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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if torch.cuda.is_available():
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-
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True, algorithm_type="sde-dpmsolver++")
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pipe = pipe.to(
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pipe.load_lora_weights(
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@@ -167,14 +168,14 @@ with gr.Blocks(css="footer{display:none !important}", theme=theme) as demo:
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minimum=256,
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=
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)
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height = gr.Slider(
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label="Height",
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minimum=256,
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=
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)
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with gr.Row():
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guidance_scale_base = gr.Slider(
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from huggingface_hub import hf_hub_download
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DESCRIPTION = """
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# Res-Adapter :Domain Consistent Resolution Adapter for Diffusion Models
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**Demo by [ameer azam] - [Twitter](https://twitter.com/Ameerazam18) - [GitHub](https://github.com/AMEERAZAM08)) - [Hugging Face](https://huggingface.co/ameerazam08)**
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This is a demo of https://huggingface.co/jiaxiangc/res-adapter LORAs by ByteDance
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"""
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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if torch.cuda.is_available():
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#Lykon/dreamshaper-xl-1-0
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pipe = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0',)# torch_dtype=torch.float16, variant="safetensors")
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True, algorithm_type="sde-dpmsolver++")
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pipe = pipe.to(device)
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pipe.load_lora_weights(
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minimum=256,
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=512,
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)
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height = gr.Slider(
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label="Height",
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minimum=256,
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=512,
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)
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with gr.Row():
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guidance_scale_base = gr.Slider(
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