programasweights

仓库创建 2026年7月4日最近提交 22 天前SkillHot 收录 22 天前
▸ 精选理由

适合低延迟或离线的文本分类与标注场景。

▸ 风险提示

编译步骤依赖托管 API 与外部服务,可能需账号和网络请求。

这个 Skill 做什么

把自然语言规范编译为本地运行的微型神经函数。

把自然语言的规则编译成一个能本地运行的小型“神经函数”(ProgramAsWeights,PAW),用来做模糊文本分类、字段抽取、格式修复、近似匹配等任务。适合那些正则太弱但又不想每次都调用大模型的场景——既快又省钱。特别点在于只需在托管端编译一次,之后这个小函数就能离线、本地长期运行。

▸ 展开 SKILL.md 英文原文

Compile a natural-language spec into a tiny neural function that runs locally with ProgramAsWeights (PAW). Use it for fuzzy text-in / text-out tasks that a regex can't handle but that are too slow, costly, or overkill to send to a full LLM on every item - classify, categorize, label, or tag text (sentiment, urgency, intent, topic, spam, support tickets, ALERT vs QUIET log lines); extract fields from messy text (emails, names, dates, IDs, invoice numbers); repair or normalize formats (broken JSON, dates); fuzzy or typo-tolerant matching, near-duplicate detection, and deduplication; map a misspelled value to the closest option; semantic search; log and error triage; and intent routing. Compile once on the hosted API, then run the function locally and offline via the Python or browser/JavaScript SDK; cheaper and faster than calling a large model per item. Not for long-form generation, open-ended chat, writing code, or multi-step reasoning.

开发编程ProgramAsWeights离线神经函数文本分类通用
0
Stars
0
Forks
1
仓库内 Skill
+0
7 日增星
安装 / 使用
给你的 Agent 一句话(通用)
帮我安装这个 skill:https://raw.githubusercontent.com/tolimcn7786/skills/main/skills/programasweights/SKILL.md
或 curl 直取 SKILL.md
curl -fsSL "https://raw.githubusercontent.com/tolimcn7786/skills/main/skills/programasweights/SKILL.md"
SKILL.MD 节选查看完整文件 ↗
# ProgramAsWeights (PAW)

ProgramAsWeights compiles a short natural-language spec into a tiny neural function
("neural software") that takes one text input and returns one text output and runs
locally. You compile once on the hosted API; the resulting function then runs locally
and offline forever.

- Website: https://programasweights.com
- Docs: https://programasweights.readthedocs.io

## When to use this

Reach for PAW when a task is fuzzy `text -> text` and you want it cheap, fast, local,
and repeatable:

- **Classification / categorization** - sentiment, urgency, intent, topic, spam, or `ALERT` vs `QUIET` log lines.
- **Extraction** - pull emails, names, dates, IDs, or fields out of mess
via SKILL·HOT · 数据来自 GitHub 公开信息 · 原文版权归作者所有