Decoder-only Transformer-based Model

A Decoder-only Transformer-based Model is a transformer model that is a decoder-only neural network (that solely relies on a decoder components).

• Context:
  • It can (typically) be employed in natural language generation tasks.
  • It can generate text in an autoregressive manner, where each new output is conditioned on the previous outputs.
  • It can (often) use techniques such as masked self-attention to focus on already generated elements while predicting the next element in a sequence.
  • It can be less suited for tasks requiring an understanding of input context, as it lacks an encoder component.
  • ...
• Example(s):
  • GPT (Generative Pre-trained Transformer) models, such as GPT-3 and GPT-4.
  • Decoder-only Language Models used in creative writing applications.
  • ...
• Counter-Example(s):
  • Encoder-only Neural Network Model.
  • Encoder-Decoder Neural Network Model.
• See: Autoregressive Model, Natural Language Generation, Masked Self-Attention, Transformer Architecture.

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