Update app.py

app.py

@@ -7,22 +7,27 @@ from diffusers import DiffusionPipeline
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
+# model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
+
+MODEL_OPTIONS = [
+    ("stabilityai/sdxl-turbo", "SDXL Turbo (Быстро)"),
+    ("CompVis/stable-diffusion-v1-4", "Stable Diffusion v1-4 (Классика)"),
+    ("Qwen/Qwen-Image", "Топ модель, но долго"),
+]
+DEFAULT_MODEL_ID = "stabilityai/sdxl-turbo"
 
 if torch.cuda.is_available():
     torch_dtype = torch.float16
 else:
     torch_dtype = torch.float32
 
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = pipe.to(device)
-
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
 
 # @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
+    model_id,  # Добавил
     prompt,
     negative_prompt,
     seed,
@@ -37,6 +42,10 @@ def infer(
         seed = random.randint(0, MAX_SEED)
 
     generator = torch.Generator().manual_seed(seed)
+    
+    pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
+    
 
     image = pipe(
         prompt=prompt,
@@ -68,6 +77,12 @@ with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown(" # Text-to-Image Gradio Template")
 
+         model_id = gr.Dropdown(
+            choices=[m[0] for m in MODEL_OPTIONS],
+            label="Model",
+            value=DEFAULT_MODEL_ID,
+        )
+        
         with gr.Row():
             prompt = gr.Text(
                 label="Prompt",
@@ -86,7 +101,8 @@ with gr.Blocks(css=css) as demo:
                 label="Negative prompt",
                 max_lines=1,
                 placeholder="Enter a negative prompt",
-                visible=False,
+                visible=True,
+                value="dog, cat"
             )
 
             seed = gr.Slider(
@@ -138,6 +154,7 @@ with gr.Blocks(css=css) as demo:
         triggers=[run_button.click, prompt.submit],
         fn=infer,
         inputs=[
+            model_id,
             prompt,
             negative_prompt,
             seed,