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.
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- 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.
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- Counter-Example(s):
- See: Autoregressive Model, Sequence-to-Sequence Model, Attention Mechanism in Neural Networks.