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test gradio
Browse files
app.py
CHANGED
@@ -4,19 +4,34 @@ from diffusers import StableDiffusion3ControlNetPipeline, SD3ControlNetModel, Un
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from huggingface_hub import login
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import os
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import spaces
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from diffusers import
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from diffusers
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# Log in to Hugging Face with your token
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token = os.getenv("HF_TOKEN")
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login(token=token)
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controlnet = SD3ControlNetModel.from_pretrained("alimama-creative/SD3-Controlnet-Softedge", torch_dtype=torch.float16)
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pipe.to("cuda", torch.float16)
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@spaces.GPU
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def generate_image(prompt, reference_image, controlnet_conditioning_scale):
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from huggingface_hub import login
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import os
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import spaces
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from diffusers.utils import load_image, make_image_grid
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import torch
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from diffusers import StableDiffusionXLAdapterPipeline,T2IAdapter
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from diffusers.models import T2IAdapter
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from diffusers.schedulers import UniPCMultistepScheduler
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# Log in to Hugging Face with your token
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token = os.getenv("HF_TOKEN")
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login(token=token)
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# Load the T2I-Style Adapter and the SDXL pipeline
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adapter = T2IAdapter.from_pretrained("TencentARC/t2i-adapter-style-sdxl")
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pipe = StableDiffusionXLAdapterPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-base-1.0",
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adapter=adapter,
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)
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# Set up the scheduler and device
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pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
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pipe.to("cuda", torch.float16)
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# controlnet = SD3ControlNetModel.from_pretrained("alimama-creative/SD3-Controlnet-Softedge", torch_dtype=torch.float16)
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#
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# pipe = StableDiffusion3ControlNetPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", controlnet=controlnet)
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# pipe.to("cuda", torch.float16)
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@spaces.GPU
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def generate_image(prompt, reference_image, controlnet_conditioning_scale):
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