Update app.py

app.py

@@ -6,11 +6,15 @@ config = PeftConfig.from_pretrained("zeyadusf/FlanT5Summarization-samsum")
 base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large")
 model = PeftModel.from_pretrained(base_model, "zeyadusf/FlanT5Summarization-samsum")
 tokenizer = AutoTokenizer.from_pretrained("zeyadusf/FlanT5Summarization-samsum")
+
+# Define the summarization function
 def summarize(text):
     inputs = tokenizer(text, return_tensors="pt", truncation=True)
-    summary_ids = model.generate(inputs.input_ids, max_length=512, min_length=64, length_penalty=2.0, num_beams=4, early_stopping=True)
+    # Access the base model's generate method
+    summary_ids = model.base_model.generate(inputs.input_ids, max_length=512, min_length=64, length_penalty=2.0, num_beams=4, early_stopping=True)
     return tokenizer.decode(summary_ids[0], skip_special_tokens=True)
 
 # Define the Gradio interface
 iface = gr.Interface(fn=summarize, inputs="text", outputs="text", title="Summarization with PEFT")
 iface.launch()
+