Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 from transformers import T5ForConditionalGeneration, AutoTokenizer
 
 st.title("SpellCorrectorT5")
-st.markdown('SpellCorrectorT5 is a fine-tuned version of **pre-trained t5-small model** modelled on randomly selected 50000 sentences modified by [imputing random noises/errors](random_noiser.py) and trained using transformers. It not only looks for _spelling errors but also looks for the semantics_ in the sentence and suggest other possible words for the incorrect word.')
+st.markdown('SpellCorrectorT5 is a fine-tuned version of **pre-trained t5-small model** modelled on randomly selected 50000 sentences modified by [imputing random noises/errors](./random_noiser.py) and trained using transformers. It not only looks for _spelling errors but also looks for the semantics_ in the sentence and suggest other possible words for the incorrect word.')
 ttokenizer = AutoTokenizer.from_pretrained("./")
 tmodel = T5ForConditionalGeneration.from_pretrained('./')