Update app.py

app.py

@@ -78,7 +78,7 @@ def get_examples(examples_dir: str = "assets/examples/ghibli-fine-tuned-sd-2.1")
     return ans
 
 def create_demo(
-    model_name: str = "danhtran2mind/ghibli-fine-tuned-sd-2.1",
+    model_name: str = "danhtran2mind/Ghibli-Stable-Diffusion-2.1-Base-finetuning",
     device: str = "cuda" if torch.cuda.is_available() else "cpu",
 ):
     # Convert device string to torch.device
@@ -179,13 +179,13 @@ def create_demo(
 
     badges_text = r"""
     <div style="text-align: center; display: flex; justify-content: left; gap: 5px;">
-    <a href="https://huggingface.co/spaces/danhtran2mind/ghibli-fine-tuned-sd-2.1"><img src="https://img.shields.io/static/v1?label=%F0%9F%A4%97%20Hugging%20Face&message=Space&color=orange"></a>
+    <a href="https://huggingface.co/spaces/danhtran2mind/Ghibli-Stable-Diffusion-Synthesis"><img src="https://img.shields.io/static/v1?label=%F0%9F%A4%97%20Hugging%20Face&message=Space&color=orange"></a>
     </div>
     """.strip()
 
     with gr.Blocks() as demo:
         gr.Markdown("# Ghibli-Style Image Generator")
-        gr.Markdown(badges_text)
+        gr.HTML(badges_text)
         gr.Markdown("Generate images in Ghibli style using a fine-tuned Stable Diffusion model. Select an example below to load a pre-generated image or enter a prompt to generate a new one.")
         gr.Markdown("""**Note:** For CPU inference, execution time is long (e.g., for resolution 512 × 512) with 50 inference steps, time is approximately 1,700 seconds for 1 CPU core and 1,200 seconds for 2 CPUs).""")
 
@@ -231,7 +231,7 @@ if __name__ == "__main__":
             default=False, metadata={"help": "Use local model path instead of Hugging Face model."}
         )
         model_name: str = dataclasses.field(
-            default="danhtran2mind/ghibli-fine-tuned-sd-2.1",
+            default="danhtran2mind/Ghibli-Stable-Diffusion-2.1-Base-finetuning",
             metadata={"help": "Model name or path for the fine-tuned Stable Diffusion model."}
         )
         device: str = dataclasses.field(
@@ -251,7 +251,7 @@ if __name__ == "__main__":
 
     # Set model_name based on local_model flag
     if args.local_model:
-        args.model_name = "ghibli-fine-tuned-sd-2.1"
+        args.model_name = "Ghibli-Stable-Diffusion-2.1-Base-finetuning"
 
     demo = create_demo(args.model_name, args.device)
     demo.launch(server_port=args.port, share=args.share)