Update app.py

[ADD] Add model_repo_id func

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_repo_id, 
     prompt,
     negative_prompt,
     seed,
@@ -35,7 +36,10 @@ def infer(
 ):
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
-
+        
+    pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
+    
     generator = torch.Generator().manual_seed(seed)
 
     image = pipe(
@@ -69,6 +73,13 @@ with gr.Blocks(css=css) as demo:
         gr.Markdown(" # Text-to-Image Gradio Template")
 
         with gr.Row():
+            model_repo_id = gr.Text(
+                label="model_repo_id",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter your model_repo_id",
+                container=False,
+            )
             prompt = gr.Text(
                 label="Prompt",
                 show_label=False,
@@ -138,6 +149,7 @@ with gr.Blocks(css=css) as demo:
         triggers=[run_button.click, prompt.submit],
         fn=infer,
         inputs=[
+            model_repo_id,
             prompt,
             negative_prompt,
             seed,