Create app.py

app.py

@@ -0,0 +1,20 @@
+import gradio as gr
+import tensorflow as tf
+
+model = tf.keras.models.load_model('toxicity.h5')
+
+def score_comment(comment):
+    vectorized_comment = vectorizer([comment])
+    results = model.predict(vectorized_comment)
+
+    text = ''
+    for idx, col in enumerate(df.columns[2:]):
+        text += '{}: {}\n'.format(col, results[0][idx]>0.5)
+
+    return text
+
+interface = gr.Interface(fn=score_comment,
+                         inputs=gr.Textbox(lines=2, placeholder='Comment to score'),
+                        outputs='text')
+
+interface.launch()