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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

  • Skills
  • AI research
  • 0

What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

  1. Install the skill (command above).
  2. In Claude Code, describe what you need - the skill turns on by itself when the context fits.
  3. No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/mamba-architecture && curl -fsSL https://doutorai.pt/data/lib/skills__mamba-architecture.md -o .claude/skills/mamba-architecture/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

---
name: mamba-architecture
description: 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.
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Model Architecture, Mamba, State Space Models, SSM, Linear Complexity, Long Context, Efficient Inference, Hardware-Aware, Alternative To Transformers]
dependencies: [mamba-ssm, torch, transformers, causal-conv1d]
---

# Mamba - Selective S

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