Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
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app.py
CHANGED
@@ -3,7 +3,7 @@ import gradio as gr
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import torch
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import numpy as np
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import random
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from diffusers import StableDiffusion3Pipeline, AutoencoderKL, SD3Transformer2DModel,
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import spaces
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from diffusers.utils import load_image
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from PIL import Image
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@@ -66,8 +66,6 @@ if torch.cuda.is_available():
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pipe = StableDiffusion3Pipeline.from_pretrained(repo, vae=vae, transformer=transformer, tokenizer_3=tokenizer_3, text_encoder_3=text_encoder_3, torch_dtype=torch.float16).to("cuda")
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pipe2 = StableDiffusion3Img2ImgPipeline.from_pretrained(repo, vae=vae, transformer=transformer, tokenizer_3=tokenizer_3, text_encoder_3=text_encoder_3, torch_dtype=torch.float16).to("cuda")
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pipe.scheduler = FlowMatchEulerDiscreteScheduler.from_config(pipe.scheduler.config)
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pipe2.scheduler = FlowMatchEulerDiscreteScheduler.from_config(pipe.scheduler.config)
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# Function
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@spaces.GPU()
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import torch
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import numpy as np
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import random
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from diffusers import StableDiffusion3Pipeline, AutoencoderKL, SD3Transformer2DModel, StableDiffusion3Img2ImgPipeline
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import spaces
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from diffusers.utils import load_image
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from PIL import Image
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pipe = StableDiffusion3Pipeline.from_pretrained(repo, vae=vae, transformer=transformer, tokenizer_3=tokenizer_3, text_encoder_3=text_encoder_3, torch_dtype=torch.float16).to("cuda")
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pipe2 = StableDiffusion3Img2ImgPipeline.from_pretrained(repo, vae=vae, transformer=transformer, tokenizer_3=tokenizer_3, text_encoder_3=text_encoder_3, torch_dtype=torch.float16).to("cuda")
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# Function
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@spaces.GPU()
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