Mamba Architecture
원문: mamba-architecture
State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.
무엇을 하나요
Mamba Selective State Space Models Quick start Mamba is a state space model architecture achieving O(n) linear complexity for sequence modeling. Installation : Prerequisites : Linux, NVIDIA GPU, PyTorch 1.12+, CUDA 11.6+ Basic usage (Mamba block): Common workflows Workflow 1: Language model with Mamba 2 Complete LM with generation : Workflow 2: Use pretrained Mamba models Load from HuggingFace : Available models : state spaces/mamba 130m state spaces/mamba 370m state spaces/mamba 790m state spaces/mamba 1.4b state spaces/mamba 2.8b Workflow 3: Mamba 1 vs Mamba 2 Mamba 1 (smaller state): Mamba 2 (multi head, larger state): Key differences : State size : Mamba 1 (d state=16) vs Mamba 2 (d stat…
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