qg

app.py

@@ -1,4 +1,8 @@
 import os
+
+os.system("pip install -U transformers==3.0.0")
+os.system("python -m nltk.downloader punkt")
+
 import gradio as gr
 import pandas as pd
 from question_generation.pipelines import pipeline
@@ -7,8 +11,6 @@ import docx2txt
 qa_list = []
 def process_file(Notes):
 
-  os.system("pip install -U transformers==3.0.0")
-  os.system("python -m nltk.downloader punkt")
   nlp = pipeline("question-generation", model="valhalla/t5-small-qg-prepend", qg_format="prepend")
   
   target_word_doc = Notes.name