AI Fine‑Tuning Code Dataset Creation Tool

Curate, clean, and package high-quality code datasets for model fine-tuning and continual training pipelines.

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Pipeline highlights

  • Source ingestion for Git, archives, and first-party repositories
  • Deduplication, language bucketing, and license-aware filtering
  • Extensible transforms for tokenization, sanitization, and tagging
  • Metadata-rich outputs compatible with JSONL, Parquet, and vector storage

Built for teams

  • Command-line interface with reusable pipeline templates
  • REST hooks for integrating orchestrators or scheduling systems
  • Quality dashboards to inspect samples, metrics, and coverage
  • Configurable retention, anonymization, and governance guardrails

Preview the workflow

Use modular stages to control ingestion, cleaning, and export processes. Policies ensure only approved licenses and sources feed downstream models.

Stay in the loop

Tell us about your use case to influence the roadmap, integrations, and defaults.

Contact Posterity Labs