Update app.py

app.py

@@ -1,22 +1,19 @@
 import streamlit as st
 from transformers import pipeline
 
+#model = AutoModelForSeq2SeqLM.from_pretrained("t5-base")
+#tokenizer = AutoTokenizer.from_pretrained("t5-base")
 classifier = pipeline("translation", model="t5-base")
 def main():
-    st.title("Text generation")
+    st.title("Text translation")
 
     with st.form("text_field"):
-        question = "What is 42?"
-        context = "42 is the answer to life, the universe and everything"
-        input = f"question: {question} context: {context}"
-        encoded_input = tokenizer([input],
-                                     return_tensors='pt',
-                                     max_length=512,
-                                     truncation=True)
-        output = model.generate(input_ids = encoded_input.input_ids,
-                                    attention_mask = encoded_input.attention_mask)
-        output = tokenizer.decode(output[0], skip_special_tokens=True)
-        print(output)
-        
+        text = st.text_area('enter some text:')
+        # clicked==True only when the button is clicked
+        clicked = st.form_submit_button("Submit")
+        if clicked:
+          results = classifier([text])
+          st.json(results)
+
 if __name__ == "__main__":
     main()