Update app.py

app.py

@@ -1,5 +1,5 @@
 import streamlit as st
-from transformers import pipeline, T5ForConditionalGeneration
+from transformers import pipeline, T5ForConditionalGeneration, T5Tokenizer
 from peft import get_peft_model, LoraConfig
 
 # Define the same LoRA configuration used during fine-tuning
@@ -11,11 +11,12 @@ lora_config = LoraConfig(
     bias="none"
 )
 
-# Load the model from Hugging Face's hub
+# Load the model and tokenizer from Hugging Face's hub
 model = get_peft_model(T5ForConditionalGeneration.from_pretrained("danrdoran/flan-t5-simplified-squad"), lora_config)
+tokenizer = T5Tokenizer.from_pretrained("danrdoran/flan-t5-simplified-squad")
 
 # Set up the Hugging Face pipeline for text2text-generation task
-model_pipeline = pipeline("text2text-generation", model=model)
+model_pipeline = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
 
 # Streamlit app UI
 st.title("AI English Tutor")