To set up a Transformer-based text generator in TensorFlow, you can use the tf.keras API to build the model, train it, and generate text. Here is the code you can refer to:
In the above code, we are using:
- Prepare your dataset: Tokenize and preprocess text data.
- Define the Transformer architecture Using layers like MultiHeadAttention, Dense, and Embedding.
- Compile and train the model: Fit it on your prepared dataset.
- Generate text: Use a decoding loop to predict word-by-word.
Hence, this approach provides a basic starting point; for complex tasks, you can expand with pre-trained embeddings or additional layers.