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')