AI-Research-SKILLs

插件

Comprehensive open-source library of AI research and engineering skills for any AI model. Package the skills and your claude code/codex/gemini agent will be an AI research agent with full horsepower. Maintained by Orchestra Research.

Orchestra-ResearchGitHub 公开资源索引Claude Code

安装与使用

13,055 GitHub Stars23 个插件包98 项组成内容Stars 同步于 2026年9月27日

概览安装与使用包含内容源码

model-architecture

LLM architectures and implementations including LitGPT, Mamba, NanoGPT, RWKV, and TorchTitan. Use when implementing, training, or understanding transformer and alternative architectures.

Claude Code

共 23 个插件包，通过下方列表选择查看。

共 5 项匹配内容，示例会单独标注；未声明归属的内容不代表插件自动包含。

distributed-llm-pretraining-torchtitan技能

Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or cu

所属插件包：model-architecture

implementing-llms-litgpt技能

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implement

所属插件包：model-architecture

mamba-architecture技能

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 desi

所属插件包：model-architecture

nanogpt技能

Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfec

所属插件包：model-architecture

rwkv-architecture技能

RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation

所属插件包：model-architecture

关于项目

原作者: Orchestra-Research
许可证: MIT
上游更新: 2026年6月16日
内容扫描: 2026年9月27日

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