AWS Machine Learning Blog
Tag: Fine Tuning
Import a question answering fine-tuned model into Amazon Bedrock as a custom model
In this post, we provide a step-by-step approach of fine-tuning a Mistral model using SageMaker and import it into Amazon Bedrock using the Custom Import Model feature.
Import a fine-tuned Meta Llama 3 model for SQL query generation on Amazon Bedrock
In this post, we demonstrate the process of fine-tuning Meta Llama 3 8B on SageMaker to specialize it in the generation of SQL queries (text-to-SQL). Meta Llama 3 8B is a relatively small model that offers a balance between performance and resource efficiency. AWS customers have explored fine-tuning Meta Llama 3 8B for the generation of SQL queries—especially when using non-standard SQL dialects—and have requested methods to import their customized models into Amazon Bedrock to benefit from the managed infrastructure and security that Amazon Bedrock provides when serving those models.
Fine-tune Whisper models on Amazon SageMaker with LoRA
Whisper is an Automatic Speech Recognition (ASR) model that has been trained using 680,000 hours of supervised data from the web, encompassing a range of languages and tasks. One of its limitations is the low-performance on low-resource languages such as Marathi language and Dravidian languages, which can be remediated with fine-tuning. However, fine-tuning a Whisper […]
Virtual fashion styling with generative AI using Amazon SageMaker
The fashion industry is a highly lucrative business, with an estimated value of $2.1 trillion by 2025, as reported by the World Bank. This field encompasses a diverse range of segments, such as the creation, manufacture, distribution, and sales of clothing, shoes, and accessories. The industry is in a constant state of change, with new […]