Deciding how to fine-tune AI models for specific tasks.
LLM Fine-Tuning Strategist
LoRA, QLoRA, RLHF, DPO, alignment strategies
Best for
- ▸Deciding between LoRA vs full fine-tuning for domain adaptation tasks
- ▸Designing RLHF pipelines for AI safety alignment in production systems
- ▸Optimizing QLoRA configurations for memory-constrained GPU environments
- ▸Evaluating ROI of fine-tuning vs RAG for enterprise knowledge injection
What you'll get
- ▸Structured decision framework comparing LoRA vs full fine-tuning with specific parameter recommendations and cost estimates
- ▸Step-by-step training pipeline design with dataset curation strategy, hyperparameter ranges, and evaluation benchmarks
- ▸RLHF implementation roadmap with reward model architecture and human feedback collection workflow
Clear problem definition including current model performance gaps, budget constraints, and specific behavioral changes needed from the model.
Detailed fine-tuning strategy with method selection, dataset requirements, evaluation metrics, and cost-performance projections.
What's inside
“You are a Senior LLM Fine-Tuning Strategist. You guide organizations through fine-tuning decisions by systematically evaluating alternatives, selecting optimal methods, and planning production deployment. * Refuse fine-tuning as first solution, exhaust prompt engineering and RAG first; recommend fin...”
Covers
Not designed for ↓
- ×Teaching new factual knowledge to models (use RAG instead)
- ×Basic prompt engineering or few-shot examples
- ×Training models from scratch or pre-training
- ×Fine-tuning proprietary models like GPT-4 (API limitations apply)
SupaScore
89.38▼
Evidence Policy
Standard: no explicit evidence policy.
Research Foundation: 8 sources (5 academic, 2 official docs, 1 paper)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
v5.5 final distill
Pipeline v4: rebuilt with 3 helper skills
Initial release
Works well with
Need more depth?
Specialist skills that go deeper in areas this skill touches.
Common Workflows
Production Fine-tuning Pipeline
End-to-end workflow from fine-tuning strategy through dataset creation, training execution, and production deployment
© 2026 Kill The Dragon GmbH. This skill and its system prompt are protected by copyright. Unauthorised redistribution is prohibited. Terms of Service · Legal Notice