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Browse files- model/animagine_xl.py +29 -27
model/animagine_xl.py
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@@ -1,45 +1,47 @@
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from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
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import torch
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def generate_animagine_xl(prompt: str):
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model_id = "Linaqruf/animagine-xl"
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pipe = StableDiffusionXLPipeline.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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use_safetensors=True,
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variant="fp16"
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)
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pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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pipe = pipe.to("cuda")
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image = pipe(prompt=prompt, width=1024, height=1024).images[0]
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image.save("output_animagine_xl.png")
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print("โ
์ ์ฅ ์๋ฃ: output_animagine_xl.png")
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return image
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if __name__ == "__main__":
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prompt = "๊ทธ๋
๋ฅผ ๋ฐ๋ผ๋ณด๋ ํ ๋จ์์ ์ผ๋ง"
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generate_animagine_xl(prompt)
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# from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
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# import torch
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# def generate_animagine_xl(prompt: str):
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# model_id = "Linaqruf/animagine-xl"
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# use_fp16 = torch.cuda.is_available()
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# pipe = StableDiffusionXLPipeline.from_pretrained(
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# model_id,
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# torch_dtype=torch.float16
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# use_safetensors=True,
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# variant="fp16"
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# )
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# pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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#
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# pipe = pipe.to(device)
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# image = pipe(prompt=prompt, width=1024, height=1024).images[0]
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# image.save("output_animagine_xl.png")
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# return image
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# if __name__ == "__main__":
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# prompt = "๊ทธ๋
๋ฅผ ๋ฐ๋ผ๋ณด๋ ํ ๋จ์์ ์ผ๋ง"
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# generate_animagine_xl(prompt)
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# from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
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# import torch
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# def generate_animagine_xl(prompt: str):
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# model_id = "Linaqruf/animagine-xl"
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# pipe = StableDiffusionXLPipeline.from_pretrained(
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# model_id,
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# torch_dtype=torch.float16,
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# use_safetensors=True,
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# variant="fp16"
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# )
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# pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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# pipe = pipe.to("cuda")
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# image = pipe(prompt=prompt, width=1024, height=1024).images[0]
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# image.save("output_animagine_xl.png")
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# print("โ
์ ์ฅ ์๋ฃ: output_animagine_xl.png")
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# return image
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# if __name__ == "__main__":
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# prompt = "๊ทธ๋
๋ฅผ ๋ฐ๋ผ๋ณด๋ ํ ๋จ์์ ์ผ๋ง"
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# generate_animagine_xl(prompt)
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from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
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import torch
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# (1) ๋ชจ๋ธ๊ณผ ์ค์ผ์ค๋ฌ๋ฅผ ์ ์ญ์์ ํ ๋ฒ๋ง ์ด๊ธฐํ
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model_id = "Linaqruf/animagine-xl"
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pipe = StableDiffusionXLPipeline.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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use_safetensors=True,
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variant="fp16"
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)
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pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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pipe = pipe.to("cuda") # ๋๋ "cpu"๋ก ๋ณ๊ฒฝ ๊ฐ๋ฅ
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# (2) ์ด๋ฏธ์ง ์์ฑ ํจ์
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def generate_animagine_xl(prompt: str):
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image = pipe(prompt=prompt, width=1024, height=1024).images[0]
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image.save("output_animagine_xl.png")
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print("โ
์ ์ฅ ์๋ฃ: output_animagine_xl.png")
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return image
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if __name__ == "__main__":
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prompt = "๊ทธ๋
๋ฅผ ๋ฐ๋ผ๋ณด๋ ํ ๋จ์์ ์ผ๋ง"
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generate_animagine_xl(prompt)
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