Add PSFT Model

app.py

@@ -1,4 +1,22 @@
 import streamlit as st
+from transformers import (T5ForConditionalGeneration, AutoTokenizer, pipeline)
+import torch
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+model_path = 'erfan226/persian-t5-formality-transfer'
+model = T5ForConditionalGeneration.from_pretrained(model_path)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+pipe = pipeline(task='text2text-generation', model=model, tokenizer=tokenizer)
+
+def paraphrase(text):
+  for j in range(3):
+    out = pipe(text, encoder_no_repeat_ngram_size=4, do_sample=True, num_beams=5, max_length=128)[0]['generated_text']
+    print("Paraphrase:", out)
+
+link = st.text_area('Paste your link here...', "من با دوستام میرم بازی", height=50)
+min_length = st.sidebar.slider('حداقل طول جمله', min_value=10, max_value=100, value=50, step=10)
+max_length = st.sidebar.slider('حداکثر طول طول جمله', min_value=30, max_value=700, value=100, step=10)
+num_beams = st.sidebar.slider('طول Beam', min_value=1, max_value=10, value=5, step=1)
+out = paraphrase(link)
+st.write(out)
+# x = st.slider('Select a value')
+# st.write(x, 'squared is', x * x)