Update app.py

app.py

@@ -5,7 +5,8 @@ import torch
 from PIL import Image
 from threading import Thread
 from typing import Generator
-from liger_kernel.transformers import apply_liger_kernel_to_llama
+# liger-kernel is an optional perf optimization; skipped here for compatibility
+# from liger_kernel.transformers import apply_liger_kernel_to_llama
 
 
 MODEL_PATH = "fancyfeast/llama-joycaption-beta-one-hf-llava"
@@ -112,19 +113,6 @@ model = LlavaForConditionalGeneration.from_pretrained(
 assert isinstance(model, LlavaForConditionalGeneration), f"Expected LlavaForConditionalGeneration, got {type(model)}"
 model.eval()
 
-print("Applying liger kernel...")
-try:
-	# Attribute name varies across transformers versions
-	llm = getattr(model, "language_model", None) or getattr(model, "model", None)
-	if llm is not None:
-		apply_liger_kernel_to_llama(model=llm)
-		print("Liger kernel applied successfully!")
-	else:
-		print("Warning: Could not find language model component, skipping liger kernel.")
-		print(f"  Available attributes: {[n for n, _ in model.named_children()]}")
-except Exception as e:
-	print(f"Warning: Liger kernel failed ({e}), continuing without it.")
-
 print("Model loaded and ready!")