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app.py

@@ -1,17 +1,17 @@
 import gradio as gr
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
-from zerogpu import setup_zerogpu
+import spaces
 
 # Load model and tokenizer
 model_id = "LiquidAI/LFM2-2.6B"
-setup_zerogpu()
 model = AutoModelForCausalLM.from_pretrained(
     model_id,
     device_map="auto",  # Ensure proper device mapping for zero-gpu
 )
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 
+@spaces.GPU(duration=120)
 def chat_with_model(message, history):
     # Format conversation history
     conversation = []