Spaces:
Running
on
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Running
on
Zero
prithivMLmods
commited on
Commit
•
15a7c48
1
Parent(s):
f9db05e
Update app.py
Browse files
app.py
CHANGED
@@ -8,9 +8,11 @@
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# furnished to do so, subject to the following conditions:
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#
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# ..
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import os
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import random
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import uuid
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import gradio as gr
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import numpy as np
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@@ -20,8 +22,6 @@ import torch
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from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
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DESCRIPTION = """
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-
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-
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"""
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def save_image(img):
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@@ -54,7 +54,45 @@ if torch.cuda.is_available():
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pipe.load_lora_weights("prithivMLmods/Canopus-Realism-LoRA", weight_name="Canopus-Realism-LoRA.safetensors", adapter_name="rlms")
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pipe.set_adapters("rlms")
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pipe.to("cuda")
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@spaces.GPU(duration=60, enable_queue=True)
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def generate(
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prompt: str,
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@@ -65,18 +103,19 @@ def generate(
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height: int = 1024,
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guidance_scale: float = 3,
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randomize_seed: bool = False,
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progress=gr.Progress(track_tqdm=True),
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):
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seed = int(randomize_seed_fn(seed, randomize_seed))
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if not use_negative_prompt:
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-
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images = pipe(
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prompt=
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negative_prompt=
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width=width,
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height=height,
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guidance_scale=guidance_scale,
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@@ -103,8 +142,7 @@ footer {
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}
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'''
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with gr.Blocks(css=css,theme="prithivMLmods/theme_brief") as demo:
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with gr.Group():
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with gr.Row():
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@@ -117,6 +155,7 @@ with gr.Blocks(css=css,theme="prithivMLmods/theme_brief") as demo:
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)
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run_button = gr.Button("Run", scale=0)
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result = gr.Gallery(label="Result", columns=1, preview=True, show_label=False)
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with gr.Accordion("Advanced options", open=False):
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use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True)
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negative_prompt = gr.Text(
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@@ -136,6 +175,7 @@ with gr.Blocks(css=css,theme="prithivMLmods/theme_brief") as demo:
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visible=True
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)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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with gr.Row(visible=True):
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width = gr.Slider(
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label="Width",
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@@ -151,6 +191,7 @@ with gr.Blocks(css=css,theme="prithivMLmods/theme_brief") as demo:
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step=8,
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value=1024,
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)
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with gr.Row():
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guidance_scale = gr.Slider(
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label="Guidance Scale",
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@@ -160,6 +201,15 @@ with gr.Blocks(css=css,theme="prithivMLmods/theme_brief") as demo:
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value=3.0,
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)
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gr.Examples(
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examples=examples,
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inputs=prompt,
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@@ -174,7 +224,6 @@ with gr.Blocks(css=css,theme="prithivMLmods/theme_brief") as demo:
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outputs=negative_prompt,
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api_name=False,
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)
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-
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gr.on(
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triggers=[
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@@ -192,10 +241,12 @@ with gr.Blocks(css=css,theme="prithivMLmods/theme_brief") as demo:
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height,
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guidance_scale,
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randomize_seed,
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],
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outputs=[result, seed],
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api_name="run",
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)
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if __name__ == "__main__":
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demo.queue(max_size=40).launch()
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# furnished to do so, subject to the following conditions:
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#
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# ..
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+
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import os
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import random
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import uuid
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from typing import Tuple
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import gradio as gr
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import numpy as np
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from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
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DESCRIPTION = """
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"""
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def save_image(img):
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pipe.load_lora_weights("prithivMLmods/Canopus-Realism-LoRA", weight_name="Canopus-Realism-LoRA.safetensors", adapter_name="rlms")
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pipe.set_adapters("rlms")
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pipe.to("cuda")
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style_list = [
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{
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"name": "3840 x 2160",
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"prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
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"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
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},
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{
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"name": "2560 x 1440",
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"prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
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"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
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},
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{
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"name": "HD+",
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"prompt": "hyper-realistic 2K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
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"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
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},
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{
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"name": "Style Zero",
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"prompt": "{prompt}",
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"negative_prompt": "",
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},
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]
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styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
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DEFAULT_STYLE_NAME = "3840 x 2160"
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STYLE_NAMES = list(styles.keys())
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def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
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if style_name in styles:
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p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
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else:
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p, n = styles[DEFAULT_STYLE_NAME]
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if not negative:
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negative = ""
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return p.replace("{prompt}", positive), n + negative
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@spaces.GPU(duration=60, enable_queue=True)
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def generate(
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prompt: str,
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height: int = 1024,
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guidance_scale: float = 3,
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randomize_seed: bool = False,
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style_name: str = DEFAULT_STYLE_NAME,
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progress=gr.Progress(track_tqdm=True),
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):
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seed = int(randomize_seed_fn(seed, randomize_seed))
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positive_prompt, effective_negative_prompt = apply_style(style_name, prompt, negative_prompt)
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if not use_negative_prompt:
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effective_negative_prompt = "" # type: ignore
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images = pipe(
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prompt=positive_prompt,
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negative_prompt=effective_negative_prompt,
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width=width,
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height=height,
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guidance_scale=guidance_scale,
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}
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'''
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with gr.Blocks(css=css, theme="prithivMLmods/theme_brief") as demo:
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with gr.Group():
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with gr.Row():
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)
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run_button = gr.Button("Run", scale=0)
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result = gr.Gallery(label="Result", columns=1, preview=True, show_label=False)
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with gr.Accordion("Advanced options", open=False):
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use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True)
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negative_prompt = gr.Text(
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visible=True
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)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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with gr.Row(visible=True):
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width = gr.Slider(
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label="Width",
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step=8,
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value=1024,
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)
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with gr.Row():
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guidance_scale = gr.Slider(
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label="Guidance Scale",
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value=3.0,
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)
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style_selection = gr.Radio(
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show_label=True,
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container=True,
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interactive=True,
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choices=STYLE_NAMES,
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value=DEFAULT_STYLE_NAME,
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label="Quality Style",
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)
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gr.Examples(
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examples=examples,
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inputs=prompt,
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outputs=negative_prompt,
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api_name=False,
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)
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gr.on(
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triggers=[
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height,
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guidance_scale,
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randomize_seed,
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style_selection,
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],
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outputs=[result, seed],
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api_name="run",
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)
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if __name__ == "__main__":
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demo.queue(max_size=40).launch()
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