Update app.py

app.py

@@ -2,9 +2,6 @@ import streamlit as st
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import tensorflow as tf
 
-#for reproducability
-SEED = 64
-
 #maximum number of words in output text
 # MAX_LEN = 30
 
@@ -16,13 +13,8 @@ MAX_LEN = number
 
 if st.button('Submit'):
 
-    #get transformers
-    from transformers import TFGPT2LMHeadModel, GPT2Tokenizer
-
     tokenizer = AutoTokenizer.from_pretrained("ml6team/gpt-2-medium-conditional-quote-generator")
     model = AutoModelForCausalLM.from_pretrained("ml6team/gpt-2-medium-conditional-quote-generator")
-    tf.random.set_seed(SEED)
-    
     inputs = tokenizer.encode(input_sequence, return_tensors='pt')
 
 # generate text until the output length (which includes the context length) reaches 50