LLM Fine-Tuning: Hugging Face & SageMaker for Enterprise AI
Scale LLM fine-tuning for enterprises with Hugging Face Transformers and Amazon SageMaker AI. Leverage distributed training, cost-efficiency, and domain-specific model customization.
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Streamline SageMaker HyperPod Management with CLI & SDK
Simplify Amazon SageMaker HyperPod cluster management with the new CLI and SDK. Streamline distributed training, inference, and cluster lifecycle for AI/ML workloads.
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Enhanced AI Training: SageMaker HyperPod Operator on Kubernetes
Accelerate large-scale AI training on Kubernetes with Amazon SageMaker HyperPod training operator. Discover its fault resiliency, pinpoint recovery, and advanced monitoring for efficient, cost-effective model development across thousands of GPUs.
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SageMaker HyperPod: Blazing Fast Model Training with Tiered Checkpointing
Accelerate large-scale model training with Amazon SageMaker HyperPod’s managed tiered checkpointing. This feature optimizes checkpointing for speed and cost, integrating with PyTorch DCP for seamless implementation. Ideal for training trillion-parameter models.
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Supercharge AI: SageMaker HyperPod & Studio
Boost your AI development with Amazon SageMaker HyperPod & Studio. This powerful combination simplifies large-scale model training & inference, improving efficiency and collaboration.
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Fine-tuning DeepSeek-R1 with SageMaker HyperPod
Fine-tune DeepSeek-R1’s 671B parameters using Amazon SageMaker HyperPod recipes. Optimize cost, deployment & performance with step-by-step guide for both HyperPod & SageMaker training jobs.
