Create app.py

app.py

@@ -0,0 +1,26 @@
+
+import streamlit as st
+from transformers import AutoTokenizer
+import torch
+
+@st.cache(allow_output_mutation=True)
+def get_model():
+    tokenizer = AutoTokenizer.from_pretrained("gpt2")
+    return tokenizer
+    
+tokenizer = get_model()
+bad_words = st.text_input("Words You Do Not Want Generated", " core lemon height time ")
+
+def run_generate(bad_words):
+  bad_words = bad_words.split()
+  bad_word_ids = []
+  for bad_word in bad_words: 
+    bad_word = " " + bad_word
+    ids = tokenizer(bad_word).input_ids
+    bad_word_ids.append(ids)
+  print(bad_word_ids)
+  return bad_word_ids
+  
+if text:
+    translated_text = run_generate(bad_words)
+    st.write(translated_text if translated_text else "No translation found")