OpenRaiser
OpenRaiser/NanoResearch
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/OpenRaiser/NanoResearch --skill nanoresearch-ideation命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.
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.
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
基于 SOC 职业分类
正在显示 SKILL.md
| name | nanoresearch-ideation |
| description | Search academic literature and generate research hypotheses |
| version | 0.1.0 |
Search arXiv and Semantic Scholar for papers related to a research topic, perform gap analysis, and generate novel hypotheses.
search_arxiv: Search arXiv for paperssearch_semantic_scholar: Search Semantic Scholar for papers and citationstopic: The research topic or question to investigateProduces papers/ideation_output.json containing: