Transform customer engagement with no-code LLM fine-tuning using Amazon SageMaker Canvas and SageMaker JumpStart

By Admin 10/05/2024

AWS Machine Learning Blog Fine-tuning large language models (LLMs) creates tailored customer experiences that align with a brand’s unique voice. Amazon SageMaker Canvas and Amazon SageMaker JumpStart democratize this process, offering no-code solutions and pre-trained models that enable businesses to fine-tune LLMs without deep technical expertise, helping organizations move faster with fewer technical resources. SageMaker […]Continue reading

Interactively fine-tune Falcon-40B and other LLMs on Amazon SageMaker Studio notebooks using QLoRA

By Admin 29/06/2023

AWS Machine Learning Blog Fine-tuning large language models (LLMs) allows you to adjust open-source foundational models to achieve improved performance on your domain-specific tasks. In this post, we discuss the advantages of using Amazon SageMaker notebooks to fine-tune state-of-the-art open-source models. We utilize Hugging Face’s parameter-efficient fine-tuning (PEFT) library and quantization techniques through bitsandbytes to […]Continue reading