Update app.py

app.py

@@ -14,8 +14,8 @@ if torch.cuda.is_available():
 else:
     torch_dtype = torch.float32
 
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = pipe.to(device)
+# 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
@@ -23,6 +23,7 @@ MAX_IMAGE_SIZE = 1024
 
 # @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
+    model,
     prompt,
     negative_prompt,
     seed,
@@ -37,7 +38,16 @@ def infer(
         seed = random.randint(0, MAX_SEED)
 
     generator = torch.Generator().manual_seed(seed)
-
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+
+    if torch.cuda.is_available():
+        torch_dtype = torch.float16
+    else:
+        torch_dtype = torch.float32
+        
+    pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
+        
     image = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
@@ -68,6 +78,15 @@ with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown(" # Text-to-Image Gradio Template")
 
+
+        with gr.Row():
+            model = gr.Dropdown(
+                choices=["stabilityai/sdxl-turbo", "CompVis/stable-diffusion-v1-4"],
+                value=model_repo_id,
+                label="Model",
+                info="Choose which diffusion model to use"
+            )
+            
         with gr.Row():
             prompt = gr.Text(
                 label="Prompt",
@@ -138,6 +157,7 @@ with gr.Blocks(css=css) as demo:
         triggers=[run_button.click, prompt.submit],
         fn=infer,
         inputs=[
+            model,
             prompt,
             negative_prompt,
             seed,