Update app.py

app.py

@@ -5,11 +5,10 @@ from diffusers import DiffusionPipeline
 pipeline = None
 
 # Load the pipeline and LoRA weights
-def load_cust(base_model, models_sec):
-    global pipeline
-    pipeline = DiffusionPipeline.from_pretrained(base_model)
-    pipeline.load_lora_weights(models_sec)
+def load_cust(modelsyu):
+    pipeline = DiffusionPipeline.from_pretrained(modelsyu)
 
+    
 def generate_image(prompt, negative_prompt):
     global pipeline
     # Generate the image with the provided prompts
@@ -25,10 +24,9 @@ with gr.Blocks() as demo:
     negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter your negative prompt here")
     submit_button = gr.Button("Generate Image")
     with gr.Accordion('Load your custom models first'):
-        basem = gr.Textbox(label="Your base model")
-        secondm = gr.Textbox(label="Your LoRA model")
+        basem = gr.Textbox(label="Your Lora model")  
         exports = gr.Button("Load your models")
-        exports.click(load_cust, inputs=[basem, secondm], outputs=[])
+        exports.click(load_cust, inputs=[basem], outputs=[])
     output_image = gr.Image(label="Generated Image")
     submit_button.click(generate_image, inputs=[prompt, negative_prompt], outputs=output_image)