About Text Curation
NeMo Curator provides comprehensive text curation capabilities to prepare high-quality data for large language model (LLM) training. The toolkit includes a collection of processors for loading, filtering, formatting, and analyzing text data from various sources using a pipeline-based architecture .
Use Cases
- Clean and prepare web-scraped data from sources like Common Crawl, Wikipedia, and arXiv
- Translate multilingual corpora while preserving structured fields and machine-readable payloads
- Create custom text curation pipelines for specific domain needs
- Scale text processing across CPU and GPU clusters efficiently
Architecture
The following diagram provides a high-level outline of NeMo Curator’s text curation architecture.
Introduction
Master the fundamentals of NeMo Curator and set up your text processing environment.
Curation Tasks
Download Data
Download text data from remote sources and import existing datasets into NeMo Curator’s processing pipeline.
Process Data
Transform and enhance your text data through comprehensive processing and curation steps.