updated requirement

model.py

@@ -10,16 +10,27 @@ HF_TOKEN = os.getenv("HUGGINGFACE_TOKEN")
 if not HF_TOKEN:
     raise ValueError("Missing Hugging Face token. Set HUGGINGFACE_TOKEN as an environment variable.")
 
-# Load tokenizer and model with authentication
+# Set device
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Load tokenizer with authentication
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=HF_TOKEN)
-model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, token=HF_TOKEN, device_map="auto")
+
+# Load model with optimizations
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    token=HF_TOKEN,
+    torch_dtype=torch.float16,  # Reduce memory usage
+    low_cpu_mem_usage=True,     # Optimize loading
+    device_map="auto",         # Automatic device placement
+    offload_folder="offload"    # Offload to disk if needed
+).to(device)
 
 def generate_code(prompt: str, max_tokens: int = 256):
     """Generates code based on the input prompt."""
     if not prompt.strip():
         return "Error: Empty prompt provided."
 
-    device = "cuda" if torch.cuda.is_available() else "cpu"
     inputs = tokenizer(prompt, return_tensors="pt").to(device)
     output = model.generate(**inputs, max_new_tokens=max_tokens)
     return tokenizer.decode(output[0], skip_special_tokens=True)