Update app.py

app.py

@@ -29,6 +29,7 @@ pipe = AutoPipelineForText2Image.from_pretrained(
     torch_dtype=torch.float16,
     use_auth_token=auth_token
 )
+pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
 
 pipe=pipe.to("cuda")
 pipe.load_lora_weights(adapter_id)
@@ -106,28 +107,18 @@ def auto_prompt_correction(prompt_ui,neg_prompt_ui,disable_auto_prompt_correctio
     return prompt,neg_prompt
     
 def txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator):
+    conditioning, pooled = compel([prompt, neg_prompt])
+    
     result = pipe(
-        prompt=prompt,
-        negative_prompt=neg_prompt, 
+        prompt_embeds=conditioning[0:1],
+        pooled_prompt_embeds=pooled[0:1], 
+        negative_prompt_embeds=conditioning[1:2], 
+        negative_pooled_prompt_embeds=pooled[1:2],
         num_inference_steps = int(steps),
         guidance_scale = guidance,
         width = width,
         height = height,
         generator = generator)
-
-    if(0):
-        conditioning, pooled = compel([prompt, neg_prompt])
-        
-        result = pipe(
-            prompt_embeds=conditioning[0:1],
-            pooled_prompt_embeds=pooled[0:1], 
-            negative_prompt_embeds=conditioning[1:2], 
-            negative_pooled_prompt_embeds=pooled[1:2],
-            num_inference_steps = int(steps),
-            guidance_scale = guidance,
-            width = width,
-            height = height,
-            generator = generator)
     
     return result.images[0]
 
@@ -138,7 +129,7 @@ with gr.Blocks(css=css) as demo:
         f"""
             <div class="main-div">
               <div>
-                <h1>Emi+LCM-LoRA Demo</h1>
+                <h1>Emi + LCM-LoRA Demo</h1>
                 <!--
                 <h2>
                 Other Demos: