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Update app.py
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app.py
CHANGED
@@ -2,6 +2,7 @@ import gradio as gr
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import torch
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from diffusers import StableDiffusionXLPipeline, AutoencoderKL, KDPM2AncestralDiscreteScheduler
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from huggingface_hub import hf_hub_download
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from PIL import Image
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import requests
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from translatepy import Translator
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@@ -28,8 +29,6 @@ JS = """function () {
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}
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}"""
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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-
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# Load VAE component
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vae = AutoencoderKL.from_pretrained(
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vae_model,
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@@ -37,12 +36,14 @@ vae = AutoencoderKL.from_pretrained(
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)
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# Ensure model and scheduler are initialized in GPU-enabled function
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pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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# Function
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def generate_image(
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prompt,
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negative="low quality",
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@@ -91,7 +92,7 @@ with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
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img = gr.Image(label='Mobius Generated Image')
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with gr.Accordion("Advanced Options", open=False):
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with gr.Row():
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negative = gr.Textbox(label="Negative prompt", value="low quality
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with gr.Row():
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width = gr.Slider(
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label="Width",
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import torch
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from diffusers import StableDiffusionXLPipeline, AutoencoderKL, KDPM2AncestralDiscreteScheduler
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from huggingface_hub import hf_hub_download
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import spaces
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from PIL import Image
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import requests
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from translatepy import Translator
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}
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}"""
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# Load VAE component
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vae = AutoencoderKL.from_pretrained(
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vae_model,
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)
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# Ensure model and scheduler are initialized in GPU-enabled function
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if torch.cuda.is_available():
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pipe = StableDiffusionXLPipeline.from_pretrained(model, vae=vae, torch_dtype=torch.float16).to("cuda")
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pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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# Function
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@spaces.GPU()
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def generate_image(
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prompt,
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negative="low quality",
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img = gr.Image(label='Mobius Generated Image')
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with gr.Accordion("Advanced Options", open=False):
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with gr.Row():
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negative = gr.Textbox(label="Negative prompt", value="low quality")
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with gr.Row():
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width = gr.Slider(
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label="Width",
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