Update app.py

app.py

@@ -22,7 +22,7 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 pipeline = AutoPipelineForText2Image.from_pretrained(
     "black-forest-labs/FLUX.1-dev",
     torch_dtype=torch.bfloat16,
-    use_auth_token=HF_TOKEN  # Authenticate directly with HF token
+    use_auth_token=HF_TOKEN
 ).to(device)
 pipeline.load_lora_weights("Purz/face-projection", weight_name="purz-f4c3_p40j3ct10n.safetensors")
 pipeline.enable_model_cpu_offload()  # Optimize memory usage
@@ -66,7 +66,7 @@ def generate_images(text, selected_model):
     results = []
     for i in range(3):
         modified_text = f"{prompt_prefix}{text} variation {i+1}"
-        image = pipeline(modified_text, num_inference_steps=20).images[0]  # Faster inference
+        image = pipeline(modified_text, num_inference_steps=20).images[0]
         results.append(image)
     return results
 
@@ -146,5 +146,4 @@ with gr.Blocks(title="AI Tutor with Visuals") as demo:
         outputs=[output1, output2, output3]
     )
 
-# In Hugging Face Spaces, this variable is automatically used as the app entry point
 demo.launch()