How to Implement a Decoder-Only Transformer in TensorFlow | by Abdulkader Helwan | Feb, 2024

Large Language Models are all the rage! Remember ChatGPT, GPT-4, and Bard? These are just a few examples of these powerful tools, all powered by a special “brain” called the transformer. This design, introduced by Google in 2017, lets these bots predict the next word in a sentence, like a super fancy autocomplete. Not all language models use this tech, but big names like GPT-3, ChatGPT, GPT-4, and LaMDa rely on it to understand and respond to your prompts.

Decoder-only transformer is a special type of neural network architecture used for tasks like text generation and translation. Unlike the standard Transformer model, which has both an encoder and a decoder, this version only uses the decoder component. Let’s break it down:

Traditional Transformer:

• Encoder: Processes an input sequence (e.g., a sentence) to capture its meaning.
• Decoder: Uses the encoded information to generate a new output sequence (e.g., a translated sentence).

Decoder-only Transformer:

• No Encoder: No information about the original input sequence is explicitly provided.
• Masked Self-Attention: Used to process the previously generated sequence, allowing the model to attend to relevant parts as it builds the output.
• Word Prediction: Generates the next word in the sequence based on the current context.

Benefits of Decoder-only Transformer:

• Simpler Architecture: Requires less training data and computational resources.
• Efficient for Certain Tasks: Works well for text generation and continuation, where no external information is needed.
• Pre-training Advantage: Can leverage pre-trained language models (LLMs) like GPT-3 effectively.

Limitations of Decoder-only Transformer:

• Lacks Context Awareness: Can’t directly access information from the original input, potentially leading to less accurate or coherent outputs.
• Restricted Applicability: Not suitable for tasks like translation or summarization where understanding the input is crucial.

Examples of Decoder-only Transformers:

• GPT-3: A large language model used for text generation and continuation.