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Update app.py
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app.py
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@@ -1,25 +1,25 @@
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import gradio as gr
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import torch
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from diffusers import StableDiffusionPipeline
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from PIL import Image
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# 1. Настройка модели
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model_id = "Kolyadual/MicroMacro-GenImage-v1-tiny"
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#
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pipe = StableDiffusionPipeline.from_pretrained(
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model_id,
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torch_dtype=torch.float32,
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use_safetensors=
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)
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pipe.to("cpu")
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#
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pipe.enable_attention_slicing()
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def generate(prompt, steps, guidance):
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#
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# Но технически она просто выдаст плохой результат на кириллице
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image = pipe(
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prompt=prompt,
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num_inference_steps=int(steps),
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@@ -27,23 +27,29 @@ def generate(prompt, steps, guidance):
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).images[0]
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return image
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# 2.
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown(
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gr.Markdown("###
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with gr.Row():
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with gr.Column():
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prompt = gr.Textbox(label="
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steps = gr.Slider(
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guidance = gr.Slider(
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btn = gr.Button("Generate ✨")
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with gr.Column():
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output_img = gr.Image(label="Result")
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btn.click(fn=generate, inputs=[prompt, steps, guidance], outputs=output_img)
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# 3. Запуск
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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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import torch
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from diffusers import StableDiffusionPipeline
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# 1. Настройка модели
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model_id = "Kolyadual/MicroMacro-GenImage-v1-tiny"
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# Убираем use_safetensors=True, так как в репозитории их нет
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# Добавляем low_cpu_mem_usage для стабильности на бесплатных тарифах
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pipe = StableDiffusionPipeline.from_pretrained(
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model_id,
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torch_dtype=torch.float32,
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use_safetensors=False,
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low_cpu_mem_usage=True
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)
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pipe.to("cpu")
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# Оптимизация для CPU
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pipe.enable_attention_slicing()
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def generate(prompt, steps, guidance):
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# Генерация
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image = pipe(
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prompt=prompt,
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num_inference_steps=int(steps),
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).images[0]
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return image
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# 2. Интерфейс Gradio
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("# 🧪 MicroMacro GenImage v1 Tiny")
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gr.Markdown("### Optimized for CPU. Please use **English** prompts.")
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with gr.Row():
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with gr.Column():
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prompt = gr.Textbox(label="Prompt (EN)", placeholder="Alchemy crystal...")
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steps = gr.Slider(1, 25, 12, step=1, label="Steps")
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guidance = gr.Slider(1, 15, 7.5, step=0.5, label="Guidance Scale")
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btn = gr.Button("Generate ✨")
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with gr.Column():
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output_img = gr.Image(label="Result")
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# Примеры для быстрой проверки пользователями
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gr.Examples(
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examples=[["mystical potion, alchemy style, glowing", 12, 7.5]],
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inputs=[prompt, steps, guidance]
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)
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btn.click(fn=generate, inputs=[prompt, steps, guidance], outputs=output_img)
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if __name__ == "__main__":
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demo.launch()
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