Update app.py

app.py

@@ -1,7 +1,7 @@
 import streamlit as st
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import tensorflow as tf
-
+import torch
 #maximum number of words in output text
 # MAX_LEN = 30
 
@@ -15,7 +15,7 @@ if st.button('Submit'):
 
     tokenizer = AutoTokenizer.from_pretrained("ml6team/gpt-2-medium-conditional-quote-generator")
     model = AutoModelForCausalLM.from_pretrained("ml6team/gpt-2-medium-conditional-quote-generator")
-    inputs = tokenizer.encode(input_sequence, return_tensors='pt')
+    inputs = tokenizer.encode(input_sequence, return_tensors="pt")
 # generate text until the output length (which includes the context length) reaches 50
     #greedy_output = GPT2.generate(input_ids, max_length = MAX_LEN)
     outputs = model(**inputs)