Update app.py

app.py

@@ -1,10 +1,31 @@
 import streamlit as st
 from transformers import pipeline
 
-st.title("Test")
-test_pipeline = pipeline("sentiment-analysis")
-text = st.text_area("Enter some text")
+# Load the pre-trained Finnish model
+model_name = "TurkuNLP/bert-base-finnish-cased-v1"
+nlp = pipeline("fill-mask", model=model_name)
 
-if text:
-    out = test_pipeline(text)
-    st.json(out)
+st.title("Finnish Language Understanding App")
+
+st.write("This app demonstrates understanding of the Finnish language.")
+
+# User input
+user_input = st.text_input("Enter a sentence in Finnish:")
+
+if user_input:
+    st.write("You entered:", user_input)
+    
+    # Use the model to predict masked words (as a simple example of language understanding)
+    masked_input = user_input.replace("____", "[MASK]")
+    results = nlp(masked_input)
+
+    st.write("Predictions for the masked word:")
+    for result in results:
+        st.write(f"Prediction: {result['token_str']}, Score: {result['score']:.4f}")
+
+if st.checkbox("Show example usage"):
+    st.write("Example sentence: Hän on ____ ystävä.")
+    example_results = nlp("Hän on [MASK] ystävä.")
+    st.write("Predictions for the masked word in the example:")
+    for result in example_results:
+        st.write(f"Prediction: {result['token_str']}, Score: {result['score']:.4f}")