Dataaspirant AI-Powered Story Generator Language Model.py

import tensorflow as tf
from tensorflow.keras.layers import Embedding, LSTM, Dense, Dropout
from tensorflow.keras.models import Sequential  


# Define model architecture
model = Sequential([
    Embedding(input_dim=vocab_size, output_dim=embedding_dim),
    LSTM(units=256, return_sequences=True),
    Dropout(0.2),
    LSTM(units=256),
    Dropout(0.2),
    Dense(vocab_size, activation='softmax')
])

# Compile the model
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])