Update app.py

app.py

@@ -1,17 +1,33 @@
 import gradio as gr
 import torch
 from transformers import MarianMTModel, MarianTokenizer
+from optimum.intel import IncQuantizer
 
-# Load the model and tokenizer from the Hub
+# Load and optimize the model (quantization)
 model_name = "Dddixyy/latin-italian-translator"
+
+# Load the quantized model if available or use a regular model (quantization shown as an example)
+try:
+    # Attempt to load a quantized version if it's available
+    quantizer = IncQuantizer.from_pretrained(model_name)
+    model = quantizer.quantize()
+    print("Quantized model loaded.")
+except Exception as e:
+    print(f"Error loading quantized model: {e}")
+    model = MarianMTModel.from_pretrained(model_name)
+
+# Load tokenizer
 tokenizer = MarianTokenizer.from_pretrained(model_name)
-model = MarianMTModel.from_pretrained(model_name)
 
 # Translation function
 def translate_latin_to_italian(latin_text):
-    inputs = tokenizer(latin_text, return_tensors="pt", padding=True, truncation=True)
+    # Truncate input to 512 tokens to avoid overload (adjust as necessary)
+    inputs = tokenizer(latin_text, return_tensors="pt", padding=True, truncation=True, max_length=512)
+    
     with torch.no_grad():
         generated_ids = model.generate(inputs["input_ids"])
+
+    # Decode the generated ids into a readable translation
     translation = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
     return translation[0]