Microsoft Researchers Introduce Samba 3.8B: A Simple Mamba+Sliding Window Attention Architecture that Outperforms Phi3-mini on Major Benchmarks

Large Language Models (LLMs) face challenges in capturing complex long-term dependencies and achieving efficient parallelization for large-scale training. Attention-based models have dominated LLM architectures due to their ability to address these issues. However, they struggle with computational complexity and extrapolation to longer sequences. State Space Models (SSMs) have emerged as a promising alternative, offering linear […]

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