Decoder-only Neural Network Model

A Decoder-only Neural Network Model is a type of neural network model that exclusively utilizes a decoder architecture.

• Context:
  • It can (typically) include models that employ techniques like [[attention mechanisms
  • It can be primarily used for generating sequences or outputs based on certain types of input data.
  • It can be particularly effective in text generation, image generation, and other forms of data generation where the output is a sequence or a structured set of data.
  • It can operate by receiving an encoded form of the input and then generating the output step-by-step in an autoregressive manner.
  • ...
• Example(s):
  • Text-to-Text Decoder-Only Model: The GPT series (e.g., GPT-3) excel in generating coherent text, creating stories, or even coding based on prompts.
  • Image-to-Text Generation Decoder-Only Model: Some decoder-only models in image processing can generate descriptive captions for images.
  • Decoder-only Image Captioning Model, such as a Decoder-only Large Language Model, such as: GPT LLM.
  • ...
• Counter-Example(s):
  • Encoder-only Neural Network Model.
  • Encoder-Decoder Neural Network Model.
• See: Autoregressive Model, Sequence-to-Sequence Model, Attention Mechanism in Neural Networks.

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