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lora-qlora-recipes

Configure LoRA and QLoRA supervised fine-tuning with current best-practice hyperparameters. Use when writing or reviewing a LoRA/QLoRA training configuration, choosing rank/alpha/target modules, or deciding between LoRA, QLoRA, and full…

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What it does and how to use it

A skill that teaches Claude Code to do general tasks well. It is packaged knowledge the model uses whenever it is relevant.

  1. Install the skill (command above).
  2. In Claude Code, describe what you need - the skill turns on by itself when the context fits.
  3. No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/wshobson-agents__lora-qlora-recipes && curl -fsSL https://doutorai.pt/data/lib/skills__wshobson-agents__lora-qlora-recipes.md -o .claude/skills/wshobson-agents__lora-qlora-recipes/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

---
name: lora-qlora-recipes
description: Configure LoRA and QLoRA supervised fine-tuning with current best-practice hyperparameters. Use when writing or reviewing a LoRA/QLoRA training configuration, choosing rank/alpha/target modules, or deciding between LoRA, QLoRA, and full fine-tuning.
---

# LoRA & QLoRA Recipes

This skill assumes the routing decision already
happened - `finetuning-method-selection` should
have already pointed here because the data shape
is demonstrations (SFT), not preference pairs or
a verifiable reward signal. What follows is the
current best-practice recipe for conf

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