update app.py

app.py

@@ -21,10 +21,6 @@ import torch
 device = "cuda" if torch.cuda.is_available() else "cpu"
 torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
 model_repo = "stabilityai/sdxl-turbo"
-pipe = DiffusionPipeline.from_pretrained(
-    model_repo,
-    torch_dtype=torch_dtype
-).to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
@@ -40,6 +36,7 @@ def infer(
     height,
     guidance_scale,
     num_inference_steps,
+    model_repo=model_repo,
     progress=gr.Progress(track_tqdm=True),
 ):
     if randomize_seed:
@@ -47,6 +44,11 @@ def infer(
 
     generator = torch.Generator().manual_seed(seed)
 
+    pipe = DiffusionPipeline.from_pretrained(
+        model_repo,
+        torch_dtype=torch_dtype,
+    ).to(device)
+
     image = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
@@ -76,7 +78,18 @@ css = """
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown(" # Text2Img Gradio")
-        gr.Markdown(f" ## Model '{model_repo}'")
+        # gr.Markdown(f" ## Model '{model_repo}'")
+
+        model_dropdown = gr.Dropdown(
+            label="Select Model", 
+            choices=[
+                "stabilityai/sdxl-turbo",
+                "stabilityai/stable-diffusion-xl-base-1.0",
+                "runwayml/stable-diffusion-v1-5",
+                "SG161222/Realistic_Vision_V5.1_noVAE"
+            ], 
+            value="stabilityai/sdxl-turbo",
+        )
 
         with gr.Row():
             prompt = gr.Text(
@@ -159,6 +172,7 @@ with gr.Blocks(css=css) as demo:
             height,
             guidance_scale,
             num_inference_steps,
+            model_dropdown,
         ],
         outputs=[result, seed],
     )