mamba-architecture SKILL.md skillA
mamba-architecture from orchestra-research/ai-research-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add orchestra-research/ai-research-skills/mamba-architecture@v1.0.0Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- orchestra-research/ai-research-skills
- Path
01-model-architecture/mamba/SKILL.md- Versions recorded
- 5
- Latest version
- v1.0.0, committed Nov 20, 2025
- First version recorded
- Nov 8, 2025
- Size
- 7,368 bytes
- Repository stars
- 13,718
- License
- MIT
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.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Mamba - Selective State Space Models
## Quick start
Mamba is a state-space model architecture achieving O(n) linear complexity for sequence modeling.
**Installation**:
```bash
# Install causal-conv1d (optional, for efficiency)
pip install causal-conv1d>=1.4.0
# Install Mamba
pip install mamba-ssm
# Or both together
pip install mamba-ssm[causal-conv1d]
```
**Prerequisites**: Linux, NVIDIA GPU, PyTorch 1.12+, CUDA 11.6+
**Basic usage** (Mamba block):
```python
import torch
from mamba_ssm import Mamba
batch, length, dim = 2, 64, 16
x = torch.randn(batch, length, dim).to("cuda")
model = Mamba(
d_model=dim, # Model dimension
d_state=16, # SSM state dimension
d_conv=4, # Conv1d kernel size
expand=2 # Expansion factor
).to("cuda")
y = model(x) # O(n) complexity!
assert y.shape == x.shape
```
## Common workflows
### Workflow 1: Language model with Mamba-2
**Complete LM with generation**:
```python
from mamba_ssm.models.mixer_seq_simple import MambaLMHeadModel
from mamba_ssm.models.config_mamba import MambaConfig
import torch
# Configure Mamba-2 LM
config = MambaConfig(
d_model=1024, # Hidden dimension
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How to install
mdr add orchestra-research/ai-research-skills/mamba-architecture@sha256:51ddf99c12a472a7The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_qjw6y4owsabgqa4j)
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Versions
The registry has recorded 5 versions of this file, between Nov 8, 2025 and Nov 20, 2025, about one every 3 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2025-11-20 | 0a9ded4 | 7,368 B | A | view · diff |
| v1.0.0 | 2025-11-20 | 72c8b2c | 7,368 B | A | view · diff |
| v1.0.0 | 2025-11-20 | f38509b | 7,367 B | A | view · diff |
| v1.0.0 | 2025-11-19 | bd4461f | 7,366 B | A | view · diff |
| git:20251108.bd4d209 | 2025-11-08 | bd4d209 | 7,096 B | A | view |
Audit of the latest version
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Source
orchestra-research/ai-research-skills · 13,718 stars · license MIT · pushed 2026-10-11 · branch main
API
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