finetuning
Generates code that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, RLVR, and RLAIF trainers, including RLVR Lambda reward function and RLAIF custom prompt creation.
Install
With your agent
Install OMGSkills skill "awslabs/agent-plugins:plugins/sagemaker-ai/skills/finetuning" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/awslabs/agent-plugins /tmp/agent-plugins && ln -s /tmp/agent-plugins/plugins/sagemaker-ai/skills/finetuning ~/.claude/skills/finetuningFrom README
Prerequisites Before starting this workflow, verify: A usecasespec.md file exists If missing: Activate the use-case-specification skill first, then resume DON'T EVER offer to create a use case spec without activating the use-case-specification skill. A fine-tuning technique (SFT, DPO, RLVR, RLAIF, or CPT/RFT (for Nova)) and base model have already been selected If missing: Activate the model-selection and/or finetuning-technique skills to collect what's missing, then resume Don't make recommendations on the spot. You MUST activate the appropriate skill.
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