Decoder-Only Neural Model Architecture
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A Decoder-Only Neural Model Architecture is a neural model architecture that utilizes only the decoder component of a traditional Encoder-Decoder Architecture for generating sequences of data.
- Context:
- It can (often) leverage a Transformer-based architecture, utilizing mechanisms such as self-attention to process input sequences directly for output generation.
- It can be trained on large datasets to capture intricate patterns and relationships within the data.
- ...
- Example(s):
- Counter-Example(s):
- an Encoder-Only Model Architecture, such as a BERT Architecture.
- A Seq2Seq Model Architecture, which relies on both an encoder and a decoder for tasks such as machine translation.
- A CNN Model Architecture, which is primarily used for tasks involving image data and does not inherently generate sequences.
- See: Sequence Generation, Transformer Architecture, Natural Language Generation, Self-Attention Mechanism.