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- 来源: blogs_podcasts
- 原始来源: https://aws.amazon.com/blogs/machine-learning/accelerate-custom-llm-deployment-fine-tune-with-oumi-and-deploy-to-amazon-bedrock
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This post is cowritten by David Stewart and Matthew Persons from Oumi.
Fine-tuning open source large language models (LLMs) often stalls between experimentation and production. Training configurations, artifact management, and scalable deployment each require different tools, creating friction when moving from rapid experimentation to secure, enterprise-grade environments.
In this post, we show how to fine-tune a Llama model using Oumi on Amazon EC2 (with the option to create synthetic data using Oumi), store artifacts in Amazon S3 , and deploy to Amazon Bedrock using Custom Model Import for managed inference.…
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