finetuning-technique
Selects a fine-tuning technique (SFT, DPO, RLVR, or RLAIF) for the user's use case and validates it against the selected model's available recipes. Use when the user has decided to finetune and needs to choose a technique, or when the technique needs to be validated against a model. Requires a base model to already be selected (via model-selection skill).
Profile →npx skills add awslabs/agent-plugins --skill finetuning-technique --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Finetuning Technique Guides the user through selecting a fine-tuning technique based on their use case and validates compatibility with the selected model. ## When to Use - User has decided to finetune and needs to choose a technique - User wants to change their finetuning technique - Technique needs to be validated against a selected model ## Prerequisites - A base model has been selected (via model-selection skill). The model name and hub must be known. - A `use_case_spec.md` file exists. If not, activate the use-case-specification skill to generate it first. ## Workflow ### Step 1: Determine Finetuning Technique Consult `references/finetune_technique_selection_guide.md` to recommend the best-fit technique based on the use case and the user's needs (SFT, DPO, RLVR, RLAIF). Present the recommendation and reasoning to the user. Ask if they'd like to go with the recommendation or prefer a different technique. ### Step 2: Validate Technique Availability 1. Once the user confirms a technique, retrieve the finetuning techniques available for the selected model by running: `python finetuning-technique/scripts/get_recipes.py <model-name> <hub-name>` - This returns only the techniques t
- When to Use
- Prerequisites
- Workflow
- Step 1: Determine Finetuning Technique
- Step 2: Validate Technique Availability
- Step 3: Confirm Selections
- References
What does the finetuning-technique skill do?
Selects a fine-tuning technique (SFT, DPO, RLVR, or RLAIF) for the user's use case and validates it against the selected model's available recipes. Use when the user has decided to finetune and needs to choose a technique, or when the technique needs to be validated against a model. Requires a base model to already be selected (via model-selection skill).
How do I install it?
Run `npx skills add awslabs/agent-plugins --skill finetuning-technique --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From awslabs/agent-plugins, a repository with 850 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.