DeepSeek Harness plugin

dsh-llm-finetuning

SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k MIT)启发。

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Source facts

Repository
satan9394/dsh-llm-finetuning
Latest update
Aug 19, 2026
Category
Tools & Capabilities
GitHub stars
0
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/satan9394/dsh-llm-finetuning
Plugin: dsh-llm-finetuning
Author: satan9394

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer3 files
README.mdSource · read only

dsh-llm-finetuning

DSH(DeepSeek Harness)技能插件:LLM 微调路由与配方

先判断是否该微调(RAG/提示词出口)、方法路由(SFT/DPO/ORPO/KTO/GRPO+RLVR/CPT)、LoRA/QLoRA 配方、评估先行(eval harness)、量化导出。受 wshobson/agents(38k★ MIT)启发的中文原创精简版。

安装

dsh plugin add dsh-llm-finetuning

触发方式

描述中包含"微调 / fine-tune / LoRA / QLoRA / DPO / GRPO / RLVR / 偏好优化 / 强化训练 / eval harness"等关键词时自动触发。

能力

  • 出口优先路由(易变事实→RAG、未定行为→提示词、稳定知识→CPT+SFT)
  • 方法选型(SFT/DPO/KTO/GRPO 按数据形态)
  • LoRA/QLoRA 配方要点与评估先行纪律
  • 量化导出(FP8/NVFP4/AWQ/GGUF)与质量验证

许可

MIT