AWS Guide: How to Deploy and Fine-Tune DeepSeek Models

Amazon Web Services (AWS) has released a comprehensive guide on deploying and fine-tuning DeepSeek models. The process involves setting up a SageMaker environment, importing the model from Hugging Face, and using a Jupyter notebook to fine-tune it on custom datasets. The guide also covers deploying the model as a SageMaker endpoint for scalable inference. Key steps include launching a SageMaker Studio instance, selecting the appropriate instance type (e.g., ml.g5.2xlarge for smaller models), and using the SageMaker Training API with a DeepSeek container. Performance optimization techniques such as mixed precision training and gradient checkpointing are recommended.