Sparse Model
A Sparse Model is a neural network architecture that activates only a specific subset of its total parameters for any given token or input, utilizing routing mechanisms to achieve massive parameter scale without proportional compute costs.
Frequently Asked Questions
What is an example of a sparse model architecture?▼
A Mixture of Experts (MoE) model, where a gating router sends each token to only 2 out of 8 available expert layers.
Why are sparse models highly efficient?▼
They allow models to store vast amounts of knowledge (high parameter count) while running inference at the speed and cost of a much smaller model.
Quick Facts
- CategoryNeural Architectures
- Key ApplicationMixture of Experts (MoE) LLMs, conditional computation layers, and cost-effective inference hosting.
Coverage Trend12 Weeks
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