Individual skill
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.
tests/ext_conformance/artifacts/templates-davila7/cli-tool/components/skills/ai-research/model-architecture-mamba/SKILL.md
Source commit a177737d6df6a543d21d3b7ee6163ec715d24aa8
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- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
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- Repository stars (not skill ratings)
- 1,970
- Repository last updated
- Nov 9, 2026
- License
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- ai-agents Repository topic
- cli Repository topic
- developer-tools Repository topic
- rust Repository topic
- model-architecture Declared skill tag
- mamba Declared skill tag
- state-space-models Declared skill tag
- ssm Declared skill tag
- linear-complexity Declared skill tag
- long-context Declared skill tag
- efficient-inference Declared skill tag
- hardware-aware Declared skill tag
- alternative-to-transformers Declared skill tag
- engineering Derived category
- design Derived category
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SKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesSKILL.mdcore · 7,368 bytesreferences/architecture-details.mddoc · 5,456 bytesreferences/benchmarks.mddoc · 8,120 bytesreferences/training-guide.mddoc · 9,012 bytes
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