ud

app.py

@@ -1,9 +1,13 @@
 import streamlit as st
-from transformers import pipeline
 
-pipe=pipeline('sentiment-analysis')
+from gliner import GLiNER
+
+model = GLiNER.from_pretrained("urchade/gliner_multi")
 text=st.text_area('enter some text!')
 
-if(text):
-  out =pipe(text)
-  st.json(out)
+labels = ["person", "award", "date", "competitions", "teams"]
+
+entities = model.predict_entities(text, labels)
+
+for entity in entities:
+    print(entity["text"], "=>", entity["label"])