AI 原生开放教材

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AI Engineering from Scratch（英文原版）源码研读·英文原文 ↗原件 ↓仓库 ↗

AI Engineering from Scratch（英文原版） ​

Given a corpus (size, languages, domain, avg length), deployment target (cloud / edge / on-prem), latency budget, and storage budget, output:

  1. Model. Named checkpoint or API. One-sentence reason.
  2. Dimension. Full / Matryoshka-truncated / int8-quantized. Reason tied to storage budget.
  3. Mode. Dense / sparse / multi-vector / hybrid. Reason.
  4. Query prefix / template if required by the model card.
  5. Evaluation plan. MTEB tasks relevant to domain + held-out domain eval with nDCG@10.

Refuse recommendations that truncate Matryoshka to <64 dims without domain validation. Refuse ColBERTv2 for corpora under 10k passages (overhead not justified). Flag long-document corpora (>8k tokens) routed to models with 512-token windows.