Initial Commit

app.py

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+import tensorflow as tf
+import gradio as gr
+
+model = tf.keras.models.load_model('hate_speech.h5')
+
+def score_comment(comment):
+    vectorized_comment = vectorizer([comment])
+    results = model.predict(vectorized_comment)
+    
+    for idx, col in enumerate(df.columns[2:]):
+        if results[0][idx]>0.5:
+            return 'Hate Speech detected'
+        
+    return 'No hate speech detected'
+
+interface = gr.Interface(fn=score_comment,
+                        inputs=gr.Textbox(lines=2, placeholder='Comment to score'),
+                        outputs='text')

hate_speech.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:24dc46ba0841c81a61b48e9b04dbba3c2df4795daf5c4a06d405787ac106a326
+size 77969552