Create app.py

app.py

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+import gradio as gr
+from diffusers import StableDiffusionPipeline
+import torch
+
+model_id = "runwayml/stable-diffusion-v1-5"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
+
+def generate_image(prompt, guidance_scale=7.5, num_inference_steps=50):
+  image = pipe(prompt, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps).images[0]
+  return image
+
+with gr.Blocks() as demo:
+  with gr.Tab("Генерация"):
+    with gr.Row():
+      with gr.Column():
+        prompt_input = gr.Textbox(label="Введите описание картинки", lines=2)
+        generate_button = gr.Button(label="Сгенерировать")
+      with gr.Column():
+        image_output = gr.Image(label="Результат")
+  with gr.Tab("Настройки"):
+    with gr.Row():
+      guidance_scale_slider = gr.Slider(label="Guidance Scale (чем больше, тем больше соответствует описанию)", minimum=1, maximum=20, step=0.5, value=7.5)
+      num_inference_steps_slider = gr.Slider(label="Number of Inference Steps (чем больше, тем качественнее, но дольше)", minimum=10, maximum=100, step=10, value=50)
+
+  generate_button.click(fn=generate_image, 
+                       inputs=[prompt_input, guidance_scale_slider, num_inference_steps_slider], 
+                       outputs=image_output)
+
+demo.launch()