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README.md
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license: apache-2.0
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---
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license: apache-2.0
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datasets:
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- imdb
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metrics:
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- accuracy
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pipeline_tag: text-classification
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# LSTM Text Classification Model for Sentiment Analysis
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This repository contains a Long Short-Term Memory (LSTM) text classification model trained on the IMDB dataset for sentiment analysis. The model has achieved an accuracy of 96% on the test dataset and is available for use as a TensorFlow model.
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## Model Details
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- **Architecture**: Long Short-Term Memory (LSTM) Neural Network
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- **Dataset**: IMDB Movie Reviews (Sentiment Classification)
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- **Accuracy**: 96%
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## Usage
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You can use this model for sentiment analysis tasks. Below are some code snippets to help you get started:
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```python
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# Load the model and perform inference
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import tensorflow as tf
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model = tf.keras.models.load_model('imdb_lstm_model.h5')
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# Perform inference
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prediction = model.predict([text])
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# Get the predicted sentiment (e.g., 'Positive' or 'Negative')
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predicted_sentiment = "Positive" if prediction > 0.5 else "Negative"
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