Curates,清洗, and formats training datasets for fine-tuning—deduplication, quality filtering, and output formatting—so the resulting model actually improves on your target behavior.
Use cases
- Custom model tuning
- Domain adaptation
- Behavior refinement
Key features
- Gather and deduplicate examples
- Filter for quality and relevance
- Format as instruction-response pairs
Related
Related
3 Indexed items
Brainstorming before build
Surfaces goals, constraints, and design options before implementation so you do not paint yourself into a corner on product or UX decisions.
Library docs in the loop
Pins assistant answers to the README, changelog, and typed exports you actually ship—using MCP doc retrieval or pasted snippets—so refactors start from real signatures instead of confident guesses.
OpenAI documentation lookup
Prioritizes official OpenAI docs, model cards, and API references when you need accurate integration guidance rather than stale blog summaries.