Update app.py

app.py

@@ -1,9 +1,22 @@
+# import streamlit as st
+# from transformers import pipeline
+
+# pipe = pipeline("sentiment-analysis")
+# text = st.text_area("enter some text")
+
+# if text:
+#   out = pipe(text)
+#   st.json(out)
 import streamlit as st
-from transformers import pipeline
 
-pipe = pipeline("sentiment-analysis")
-text = st.text_area("enter some text")
+# adding the text that will show in the text box as default
+default_value = "See how a modern neural network auto-completes your text 🤗 This site, built by the    Hugging Face team, lets you write a whole document directly from your browser, and you can trigger the Transformer anywhere using the Tab key. Its like having a smart machine that completes your thoughts 😀 Get started by typing a custom snippet, check out the repository, or try one of the examples. Have fun!"
+
+sent = st.text_area("Text", default_value, height = 275)
+max_length = st.sidebar.slider("Max Length", min_value = 10, max_value=30)
+temperature = st.sidebar.slider("Temperature", value = 1.0, min_value = 0.0, max_value=1.0, step=0.05)
+top_k = st.sidebar.slider("Top-k", min_value = 0, max_value=5, value = 0)
+top_p = st.sidebar.slider("Top-p", min_value = 0.0, max_value=1.0, step = 0.05, value = 0.9)
+num_return_sequences = st.sidebar.number_input('Number of Return Sequences', min_value=1, max_value=5, value=1, step=1)
+
 
-if text:
-  out = pipe(text)
-  st.json(out)