Update app.py

app.py

@@ -1,3 +1,32 @@
+import gradio as gr
+import tensorflow as tf
+import tensorflow_text as text
+
+
+
+from huggingface_hub import from_pretrained_keras
+
+model = from_pretrained_keras("weightedhuman/fine-tuned-bert-news-classifier")
+
+
+def get_sentiment_score(text):
+  if text is not None:
+    serving_results = model \
+                .signatures['serving_default'](tf.constant(text))
+
+
+    serving_results = tf.sigmoid(serving_results['classifier'])
+        
+    serving_results_np = serving_results.numpy()
+
+    for i in range(len(serving_results_np)):
+
+        output_value = serving_results_np[i][0]
+
+        return float(output_value)
+  else:
+    return ""
+
 intf = gr.Interface(
     fn = get_sentiment_score,
     inputs = gr.Textbox(),