Pre-train BERT with Hugging Face Transformers on Habana Gaudi via AWS DL1

AI Impact Summary

The tutorial documents end-to-end pre-training of BERT-base from scratch on Habana Gaudi DL1 using Hugging Face Transformers, Optimum Habana, and Datasets, covering dataset preparation, tokenizer training, and preprocessing before MLM pretraining. It uses AWS-based hardware and the rm-runner remote launcher to orchestrate the Gaudi-based training, noting that steps 1–3 are CPU-intensive and can be run on non-Gaudi instances. This demonstrates a concrete path to cost-efficient, high-throughput NLP pretraining on Gaudi hardware, but requires careful alignment of software versions (Transformers, Optimum Habana, Datasets) and the remote execution workflow to avoid environment drift.