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Update app.py
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app.py
CHANGED
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@@ -1,16 +1,18 @@
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import gradio as gr
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import numpy as np
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import torch
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from diffusers import DiffusionPipeline
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_repo_id = "stabilityai/sdxl-turbo" #
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if torch.cuda.is_available():
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torch_dtype = torch.float16
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else:
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torch_dtype = torch.float32
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# Изначально загружаем модель по умолчанию
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pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
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pipe = pipe.to(device)
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@@ -30,17 +32,15 @@ def infer(
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):
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global model_repo_id, pipe
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#
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if model != model_repo_id:
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try:
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# Пробуем загрузить новую модель
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new_pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype)
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new_pipe = new_pipe.to(device)
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# Если успешно, то обновляем pipe и модель
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pipe = new_pipe
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model_repo_id = model
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except Exception as e:
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raise gr.Error(f"Не удалось загрузить модель {model}.
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generator = torch.Generator(device=device).manual_seed(seed)
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@@ -69,17 +69,17 @@ css = """
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}
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"""
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with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="col-container"):
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gr.Markdown(" # Text-to-Image App")
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# Вместо выпадающего списка — текстовое поле для ввода модели
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model = gr.Textbox(
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label="Model
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value="stabilityai/sdxl-turbo", # Значение по умолчанию
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interactive=True
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)
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prompt = gr.Text(
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label="Prompt",
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show_label=False,
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@@ -102,7 +102,7 @@ with gr.Blocks(css=css) as demo:
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step=1,
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value=42,
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)
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guidance_scale = gr.Slider(
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label="Guidance scale",
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minimum=0.0,
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import gradio as gr
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import numpy as np
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import random
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import torch
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from diffusers import DiffusionPipeline
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_repo_id = "stabilityai/sdxl-turbo" # Replace to the model you would like to use
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if torch.cuda.is_available():
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torch_dtype = torch.float16
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else:
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torch_dtype = torch.float32
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# Изначально загружаем модель по умолчанию (как в исходном коде)
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pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
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pipe = pipe.to(device)
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):
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global model_repo_id, pipe
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# Если пользователь ввёл новую модель, пробуем загрузить
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if model != model_repo_id:
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try:
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new_pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype)
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new_pipe = new_pipe.to(device)
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pipe = new_pipe
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model_repo_id = model
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except Exception as e:
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raise gr.Error(f"Не удалось загрузить модель '{model}'.\nОшибка: {e}")
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generator = torch.Generator(device=device).manual_seed(seed)
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}
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"""
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# Убрали выпадающее меню, заменили на текстовое поле
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with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="col-container"):
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gr.Markdown(" # Text-to-Image App")
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model = gr.Textbox(
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label="Model (repo or local path)",
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value="stabilityai/sdxl-turbo", # Значение по умолчанию
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interactive=True
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)
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prompt = gr.Text(
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label="Prompt",
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show_label=False,
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step=1,
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value=42,
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)
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guidance_scale = gr.Slider(
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label="Guidance scale",
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minimum=0.0,
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