Training patterns for autoregressive neural PDE solvers (FNO, DeepONet, CNO). Covers rollout training, noise injection for stability, multi-component loss functions (H1, frequency-sensitive, boundary-aware), per-channel normalization for coupled multi-variable systems, and the PDEBench nRMSE metric. Use when training any neural operator that predicts time-dependent PDE solutions.
日本語の概要は準備中です。原文の説明を表示しています。
huang-sh/DeepScience☆ 42026年7月15日 更新
Migrate a legacy-template SGLang cookbook page (monolithic per-model generator under docs/src/snippets/autoregressive/) onto the config-driven template (shared _deployment.jsx / _playground.jsx engines + per-model config). Use when asked to migrate, convert, or port an existing cookbook page — NOT for brand-new models (use cookbook-add-model for those). Run with /cookbook-migrate-model <Model page name, e.g. GLM-5.1>.
日本語の概要は準備中です。原文の説明を表示しています。
sgl-project/sglang☆ 3.7万2026年10月13日 更新