12 个 · 工程化 · 模型
Pax 是一个基于 Jax 的机器学习框架，用于训练大规模模型。Pax 支持先进且完全可配置的实验与并行化，并已展现出业界领先的模型 FLOP 利用率。Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.
"OpenWAM: An Open, Modular Exploration Towards Systematic World–Action Model Pretraining" 的官方仓库。Official repository for "OpenWAM: An Open, Modular Exploration Towards Systematic World–Action Model Pretraining".
将任意 LLM 转变为 Jev 风格决策模型：类型化决策、真实概率、无需训练。（持续更新）Turn any LLM into a Jev-style decision model: typed decisions, real probabilities, no training. (continue updating)
在 220k GB200 上训练前沿模型的完整脚本。"普罗米修斯从众神那里盗取火种，将其赐予人类。"Full script for training a frontier model on 220k GB200s. "Prometheus stole fire from the gods and gave it to man."
一个 Model Context Protocol (MCP) 服务器，使 AI 助手能够与 Kubernetes 集群交互，作为 AI 工具（如 Claude、Cursor 和 GitHub Copilot）与 Kubernetes 之间的桥梁A Model Context Protocol (MCP) server that enables AI assistants to interact with Kubernetes clusters. It serves as a bridge between AI tools (like Claude, Cursor, and GitHub Copilot) and Kubernetes
3D 打印骑行装备 2026：轮挡、平板支架与 AirTag 挂架3D Printable Cycling Gear 2026: Wheel Blocks, Tablet Stands & AirTag Holders
[CoLM 2026] MoANT 官方代码：面向多任务大语言模型微调的语义感知秩一专家混合模型[CoLM 2026] Official code for MoANT: Mixture-of-Rank-One-Experts with semantic-aware Intuition for Multi-task Large Language Model Finetuning
从零开始构建开源预训练 LLM，附带已发布的数据、训练代码、消融实验与结果，以高效提升模型质量。Build open pretraining LLMs from scratch with released data, training code, ablations, and results to improve model quality efficiently
用知识图谱刻画 AI/ML 模型从创建到部署的完整生命周期。Knowledge Graph to capture AI/ML model lifecycle from creation through deployments.
Same Targets, Different Computation 的代码与 artifact：后训练如何在模型各层之间划分计算Code and artifacts for Same Targets, Different Computation: how post-training divides work across model layers.
🚀 使用 Fast-LLM 加速 LLM 训练，一个面向高速、可扩展、灵活模型开发的开源库🚀 Accelerate LLM training with Fast-LLM, an open-source library for high-speed, scalable, and flexible model development.
基于 Transformer 架构的可复现研究原型，用于长周期建筑能耗预测，结合可微的热物理约束并支持跨建筑泛化A reproducible research prototype for long-horizon building energy forecasting using transformer architectures with differentiable thermal-physics constraints and cross-building generalization.