📄 中文摘要
通过 Oumi 在 Amazon EC2 上对 Llama 模型进行微调，用户可以选择使用 Oumi 创建合成数据。微调后的模型和相关工件存储在 Amazon S3 中，随后可通过自定义模型导入功能将其部署到 Amazon Bedrock，实现托管推理。这一过程简化了大规模语言模型的部署，提升了效率，适用于各种应用场景。
加速自定义 LLM 部署：使用 Oumi 微调并部署到 Amazon Bedrock
📄 English Summary
Accelerate custom LLM deployment: Fine-tune with Oumi and deploy to Amazon Bedrock
Fine-tuning a Llama model using Oumi on Amazon EC2 allows users to create synthetic data with Oumi as an option. The fine-tuned model and associated artifacts are stored in Amazon S3, and can then be deployed to Amazon Bedrock using the Custom Model Import feature for managed inference. This process streamlines the deployment of large language models, enhancing efficiency and applicability across various use cases.