Create app.py

app.py

@@ -0,0 +1,24 @@
+
+import streamlit as st
+
+from transformers import pipeline
+
+@st.cache(allow_output_mutation=True)
+def get_model(model):
+	return pipeline("fill-mask", model=model)
+
+
+text = st.text_input("Enter a text for auto completion...")
+
+history_keyword_text = st.text_input("Users's history keyword split with ','")
+
+model = st.selectbox("choose a model", ["roberta-base", "bert-base-uncased", "gpt2", "t5"])
+
+if text:
+	data_load_state = st.text('Loading...')
+	nlp = get_model(model)
+	result = nlp(text+nlp.tokenizer.mask_token)
+	data_load_state.text('Loading data...done!')
+#	for c in result:
+#		del c["token"]
+	st.table(result)