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import streamlit as st |
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from transformers import pipeline |
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import tensorflow as tf |
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import numpy as np |
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import pandas as pd |
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from tensorflow.keras.layers import TextVectorization |
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from tensorflow import keras |
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model = tf.keras.models.load_model('toxicity_model.h5') |
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df = pd.read_csv('train.csv') |
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X = df['comment_text'] |
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y = df[df.columns[2:]].values |
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MAX_FEATURES = 200000 |
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vectorizer = TextVectorization(max_tokens=MAX_FEATURES, |
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output_sequence_length=1800, |
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output_mode='int') |
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vectorizer.adapt(X.values) |
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input_str = vectorizer('I hate you.') |
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res = model.predict(np.expand_dims(input_str,0)) |
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classification = res[0].tolist() |
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st.write(classification) |