Data Scientists and ML Engineers often need to fine-tune Large Language Models (LLMs) to meet their specific business needs, which requires carefully curated and validated training data. However, if they are not familiar with the Amazon SageMaker SDK, implementing an established FMOps pipeline can be time-consuming. With Amazon SageMaker Pipelines UI, users can easily create pipelines through a drag-and-drop interface. The pipeline can include multiple steps such as data preparation, LLM fine-tuning, and model evaluation, while tracking experiments in an MLflow server.
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