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NanoResearch

github.com/OpenRaiser/NanoResearch

Skill

Added

Review

peft-fine-tuning

skills/vendor-ai-research/peft/SKILL.md

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.

70

ml-training-recipes

skills/vendor-ai-research/ml-training-recipes/SKILL.md

Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.

79

ml-paper-writing

skills/vendor-ai-research/ml-paper-writing/SKILL.md

Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.

71

academic-plotting

skills/vendor-ai-research/academic-plotting/SKILL.md

Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.

74

autoresearch

skills/vendor-ai-research/0-autoresearch-skill/SKILL.md

Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.

66

nanoresearch-writing

skills/nanoresearch-writing/SKILL.md

Draft a LaTeX research paper from all previous stage outputs

54

nanoresearch-planning

skills/nanoresearch-planning/SKILL.md

Produce an experiment blueprint from a research hypothesis

54

nanoresearch-ideation

skills/nanoresearch-ideation/SKILL.md

Search academic literature and generate research hypotheses

54

nanoresearch-experiment

skills/nanoresearch-experiment/SKILL.md

Generate a Python code skeleton from an experiment blueprint

54