> ML_ARCHITECTURE // STATE-SPACE-MODEL-MAMBA_v1.0
Selective State-Space Model (Mamba / Mamba-2)
Sub-quadratic sequence architecture featuring time-varying selection parameters and hardware-aware scan algorithms, delivering constant-memory inference and linear scaling with sequence length.
State Space Modelstextaudiotime-series
Back to All ArchitecturesArchitecture Overview
Sub-quadratic sequence architecture featuring time-varying selection parameters and hardware-aware scan algorithms, delivering constant-memory inference and linear scaling with sequence length.
Implementing Libraries
Seminal Papers
Mamba: Linear-Time Sequence Modeling with Selective State SpacesAlbert Gu, Tri Dao (2023) · arXiv preprint
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space DualityTri Dao, Albert Gu (2024) · International Conference on Machine Learning (ICML)
Architectural Limitations & Constraints
- Requires compatible deep learning framework and hardware acceleration for efficient execution.