A step-by-step guide to building an end-to-end MLOps pipeline using Amazon SageMaker Pipelines and Hugging Face Transformers. The tutorial covers fine-tuning a DistilBERT model on the IMDB dataset, with pipeline steps including data preprocessing via SKLearn, model training with the Hugging Face Estimator, model evaluation with conditional deployment logic, model registration in the SageMaker Model Registry, and serverless deployment via a Lambda step. The pipeline is fully parameterized, allowing instance types and hyperparameters to be varied without code changes.
