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.
| Field | Value |
|---|---|
| Owner | Orchestra-Research |
| Curator | Thomas Cherickal |
| Source | Orchestra-Research/AI-Research-SKILLs |
| Repo stars | 14,542 |
| License | MIT |
| Repo last push | 2026-10-11 |
Links
- Roles: quantum-ml-engineer
- Source repo: Orchestra-Research/AI-Research-SKILLs
- Same repo: axolotl, deepspeed, distributed-llm-pretraining-torchtitan, fine-tuning-openvla-oft, fine-tuning-serving-openpi, awq-quantization, gguf-quantization, gptq
- Registry seed skills for this role: quantum-ml-engineer seed skills