Overview
Data Prep Kit is an open-source toolkit designed to accelerate preparation of unstructured data for LLM development. It provides transforms, recipes, and scalable pipelines suitable for pretraining, fine-tuning, instruction tuning, and RAG workflows.
Key features
- A growing set of modular transforms covering laptop-scale to datacenter-scale processing.
- Support for multiple runtimes (Python, Ray, Spark) and integration with Kubeflow Pipelines for workflow automation.
- Rich examples, recipes, and Google Colab notebooks for quick experimentation.
- Governance and maintenance by IBM Research and LF AI & Data, with active contributor community.
Use cases
- Cleaning and transforming corpora for model training or fine-tuning.
- Building and preparing retrieval datasets and pipelines for RAG systems.
- Converting and enriching data into formats suitable for downstream model workflows.
Technical details
- Primary languages: HTML/Jupyter/Python; modular transform design for extensibility.
- License: Apache-2.0.
- Extensive docs, examples, and recipes are provided to compose end-to-end data prep pipelines.