Update app.py

app.py

@@ -1,18 +1,19 @@
 import gradio as gr
 from diffusers import DiffusionPipeline
 
-
 def generate_image(modelsyu, prompt, negative_prompt):
-    
-    modelslo = [modelsyu]   
-    pipeline = DiffusionPipeline.from_pretrained(modelslo)
+    pipeline = DiffusionPipeline.from_pretrained(modelsyu)
     pipeline.to("cpu")
-    image = pipeline(prompt, negative_prompt=negative_prompt).images[0]
+    # Check if negative_prompt is supported by the pipeline
+    if 'negative_prompt' in pipeline.parameters:
+        image = pipeline(prompt, negative_prompt=negative_prompt).images[0]
+    else:
+        image = pipeline(prompt).images[0]
     return image
 
 # Define the Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("# Text to Image Generation Custom models Demo")
+    gr.Markdown("# Text to Image Generation Custom Models Demo")
     prompt = gr.Textbox(label="Prompt", placeholder="Enter your text prompt here")
     negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter your negative prompt here")
     submit_button = gr.Button("Generate Image")