Create app.py

app.py

@@ -0,0 +1,28 @@
+import streamlit as st
+from transformers import pipeline
+
+tokenizer = AutoTokenizer.from_pretrained(
+    'airesearch/wangchanberta-base-att-spm-uncased'
+)
+model = AutoModelForSequenceClassification.from_pretrained(
+    'airesearch/wangchanberta-base-att-spm-uncased',
+    revision='finetuned@wisesight_sentiment-v1.1',
+)
+text_cls_pipeline = pipeline(task='sentiment-analysis',
+                            tokenizer=tokenizer,
+                            model=model,
+                            return_all_scores=True)
+
+def main():
+    st.title("Text")
+
+    with st.form("text_field"):
+        text = st.text_area('enter some text:')
+        # clicked==True only when the button is clicked
+        clicked = st.form_submit_button("Submit")
+        if clicked:
+          results = text_cls_pipeline([text])
+          st.json(results)
+
+if __name__ == "__main__":
+    main()