仓库/Skill 库

并行运行 Claude Code、Codex 与 Gemini，并支持彼此交接任务。面向 AI CLI 的便携 Windows 终端。Run Claude Code, Codex and Gemini side by side — and let them hand work to each other. Portable Windows terminal for AI CLIs.

大语言模型元数据的开放注册表——以单一机器可读的 models.json 提供身份、作者、模态、上下文/输出限制、能力与生命周期日期，并通过 JSON Schema 校验。CC BY 4.0Open registry of large-language-model metadata — identity, authorship, modalities, context/output limits, capabilities & lifecycle dates as one machine-readable models.json validated by JSON Schema. CC BY 4.0.

A field-adaptive academic writing Skill for Chinese and English research papers. | 面向中英文学术论文的领域自适应写作 Skill。

🛠️ 通过 Local-LLM（一款基于 BERT 模型的轻量级 Python 库）在安全环境中实现离线 NLP 工作流，确保可复现性与可靠性。🛠️ Enable offline NLP workflows with Local-LLM, a lightweight Python library for secure environments using the BERT model, ensuring reproducibility and reliability.

Run the native 284B-A13B DeepSeek-V4-Flash-0731 LLM locally on a single laptop CPU: pure C, 8 GB RAM minimum, no GPU, best TPOT 0.892 s/token. ｜ 在笔记本单颗 CPU 上本地运行原生 284B-A13B DeepSeek-V4-Flash-0731 大模型：纯 C，最低 8 GB 内存，无需 GPU，最优 TPOT 0.892 秒/token。

Tox21 多终点毒性预测：可复现的研究与推理制品（冻结模型、FastAPI 服务、已审计的安全机制）Tox21 multi-endpoint toxicity prediction: a reproducible research and inference artifact (frozen model, FastAPI service, audited security)

THIS PAPER IS FOR ENTERTAINMENT PURPOSES ONLY.この小説はフィクションであり、実在する団体または個人とは関係ありません。

轻松优化面向 AI 系统的 prompt，借助直观工具与特性提升性能🚀 Optimize your prompts for AI systems easily and boost performance with intuitive tools and features designed for better results.

《大模型推理原理与优化》：面向系统/架构/后端研发工程师的模型原理入门课，目标是通俗易懂的解释推理过程，理解原理有助于系统开发/维护工作

DP-ES 官方实现：面向 Prompt 优化的差分隐私进化策略（EMNLP 2026）。Official implementation of DP-ES: Differentially Private Evolution Strategies for Prompt Optimization (EMNLP 2026)

一个可复用的 Codex Skill，用于证据对齐、AI 与人工审稿人就绪的学术写作。A reusable Codex skill for evidence-aligned, AI- and human-reviewer-ready academic writing.

面向生产环境的、有内存约束的跨模型 KV-cache 传输，具备受保护的回退机制与可复现研究工具链。Production-oriented, memory-bounded cross-model KV-cache transfer with guarded fallback and reproducible research tooling.

Codex + DeepSeek 的任务感知推理模式路由（spec/react/weak）Task-aware reasoning-mode router for Codex + DeepSeek | Codex+DeepSeek 思维模式路由（spec/react/weak）

通过一次 wrap() 调用为 LLM 流水线构建运行时可靠性守卫，可配置地防御常见生产故障Build runtime reliability guards for LLM pipelines with one wrap() call and configurable protection against common production failures

WordPress 共享 AI 基础设施：provider 凭证、实时模型、提示词、标准化请求及 AI-Scribe 和兼容插件的使用记录。Shared AI infrastructure for WordPress: provider credentials, live models, prompts, normalised requests and usage records for AI-Scribe and compatible plugins.

论文《Controllable molecular graph generation from natural-language chemical constraints》（基于自然语言化学约束的可控分子图生成）的代码仓库。This is repository for "Controllable molecular graph generation from natural-language chemical constraints"

几何有限主义：语言与思维的几何学Geofinitism: The Geometry of Language and Thought

构建安全、有治理、可观测、成本可控的云与 AI 平台能力的实用参考框架。A practical reference framework for building secure, governed, observable, and cost-aware Cloud & AI platform capabilities.

本代码库提供个人研究成果《Deep Learning Approach in Time Series Forecasting: Literature Review and Extension on Feature Extraction》的代码与报告存档。This repository provides code and report archive of individual research: Deep Learning Approach in Time Series Forecasting: Literature Review and Extension on Feature Extraction

The Convergence Gap 的代码与 artifact：指令微调模型何时收敛到下一 token 预测Code and artifacts for The Convergence Gap: when instruction-tuned models settle on next-token predictions.

prompt工具箱

贝叶斯统计研究语料库：面向贝叶斯统计（推断、计算、先验、模型选择、层次模型、非参数、深度贝叶斯、应用）的数据驱动、自动化校验文献综述Bayesian Statistics Research Corpus: Data-driven, auto-validated literature review for Bayesian statistics (inference, computation, priors, model selection, hierarchical, nonparametric, deep Bayesian, applications)

面向几何感知量子机器学习的可复现研究框架。A reproducible research framework for geometry-aware quantum machine learning.

生产级 LLM 网关：兼容 OpenAI 的 API，支持语义缓存，可在 Claude/OpenAI/Ollama 之间进行智能路由与成本分析。Production LLM gateway: OpenAI-compatible API, semantic caching, intelligent routing across Claude/OpenAI/Ollama, cost analytics.

使用 TurboQuant 和 MLX 在 Windows 上运行 Qwen3.5 语言模型，实现快速的本地推理。Run the Qwen3.5 language model on Windows using TurboQuant and MLX for fast local performance.

Experimental Qwen3.5-derived 752M LLM：基于 Qwen3.5 的实验性 752M 参数 LLM，采用 CPT + SFT 两阶段流程，面向编码、技术推理与指令跟随。Experimental Qwen3.5-derived 752M LLM: a two-phase CPT + SFT pipeline for coding, technical reasoning, and instruction following.

不要再重复解决同一段代码——一个本地优先的分布式推理缓存：来自真实环境的匿名兼容性证据，加上面向编码 LLM 的已验证最小示例。Stop solving the same code twice — a local-first distributed reasoning cache: anonymous compatibility evidence from real environments plus verified minimal samples for coding LLMs.

通过 MegaQwen CUDA megakernel 加速 Qwen3-0.6B 推理，在 RTX 3090 上达到 531 tok/s decode，较 HuggingFace 提升 3.9×🚀 Achieve faster Qwen3-0.6B inference with the MegaQwen CUDA megakernel, delivering 531 tok/s decode on RTX 3090—3.9x faster than HuggingFace.

大语言模型（LLM）是一种人工智能（AI）程序，能够识别并生成文本，以及执行其他任务。A large language model (LLM) is a type of artificial intelligence (AI) program that can recognize and generate text, among other tasks.

在双 RTX 3090 GPU 上以 262K 上下文长度并发流运行 Qwen3.6-27B，开发工作已迁移至 club-3090。Run Qwen3.6-27B at 262K context with concurrent streams on dual RTX 3090 GPUs. Development moved to club-3090.

本地优先、隐私至上的 AI 驱动学术写作人性化工具。AI-Powered Academic Writing Humanizer - Local-First, Privacy-Centric Solution

完全在浏览器中通过 WebAssembly 实现文档转换、检查、OCR 与翻译。保留版式的翻译，全程本地、离线优先。Convert, inspect, OCR, and translate any document entirely in the browser via WebAssembly. Layout-preserving translation, fully local, offline-first.

使用支持 macOS 和 Windows 平台的开源工具高效构建与定制机器学习模型Build and customize machine learning models efficiently with an open-source tool that supports macOS and Windows platforms.

MAI-Code 模型的官方仓库，用于发布 MAI-Code 模型版本与更新，并通过 issue 与反馈与开发者社区互动。Official repo for MAI-Code models, where we publish MAI-Code model releases and updates and engage with developer community on issues and feedback.

使用纯 C 从零构建 LLM 推理引擎，不依赖任何框架。Build an LLM inference engine from scratch in pure C with no frameworks.