update app.py

app.py

@@ -7,15 +7,15 @@ 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
 
 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)
+# 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_id,
     prompt,
     negative_prompt,
     seed,
@@ -36,6 +37,10 @@ def infer(
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
+    print(f"Model id: {model_id}")
+    pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
+
     generator = torch.Generator().manual_seed(seed)
 
     image = pipe(
@@ -68,14 +73,30 @@ with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown(" # Text-to-Image Gradio Template")
 
+        prompt = gr.Text(
+            label="Prompt",
+            show_label=False,
+            max_lines=1,
+            placeholder="Enter your prompt",
+            container=False,
+        )
+
         with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
+            model_id = gr.Text(
+                label="Model ID",
                 show_label=False,
                 max_lines=1,
-                placeholder="Enter your prompt",
+                placeholder="Enter model id",
                 container=False,
+                value="CompVis/stable-diffusion-v1-4",
             )
+            # prompt = gr.Text(
+            #     label="Prompt",
+            #     show_label=False,
+            #     max_lines=1,
+            #     placeholder="Enter your prompt",
+            #     container=False,
+            # )
 
             run_button = gr.Button("Run", scale=0, variant="primary")
 
@@ -138,6 +159,7 @@ with gr.Blocks(css=css) as demo:
         triggers=[run_button.click, prompt.submit],
         fn=infer,
         inputs=[
+            model_id,
             prompt,
             negative_prompt,
             seed,