Data Pipelines for Pre-Training

The model is a mirror. It reflects whatever data you feed it. Feed it garbage, it reflects garbage with perfect fluency.

Build 1.5 hr Python

Prerequisites: Phase 10, Lessons 01-02 (Tokenizers, Building a Tokenizer)

#Learning Objectives

  • Build a streaming data pipeline that tokenizes, chunks, shuffles, and batches terabytes of text without loading it all into memory
  • Implement data quality filters (deduplication, language detection, content filtering) used in real pre-training pipelines
  • Create fixed-length training sequences with proper attention masks and document boundary handling
  • Profile pipeline throughput to ensure the dataloader keeps up with GPU training speed
Full Access lesson

Keep going. The rest of this lesson is one step away.

Unlock all 503 lessons, video, code, quizzes and every future update. Pay in your own currency with Paystack.

The text and code of this lesson are based on AI Engineering from Scratch by Rohit Ghumare, MIT licensed.