An introduction to preparing your own dataset for LLM training
In this blog post, we provide an introduction to preparing your own dataset for LLM training. Whether your goal is to fine-tune a pre-trained model for a specific task or…
Amazon SageMaker
How Amazon trains sequential ensemble models at scale with Amazon SageMaker Pipelines
Ensemble models are becoming popular within the ML communities. They generate more accurate predictions through combining the predictions of multiple models. Pipelines can quickly be used to create and end-to-end…
Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 2: ModelBuilder
In Part 1 of this series, we introduced the newly launched ModelTrainer class on the Amazon SageMaker Python SDK and its benefits, and showed you how to fine-tune a Meta…
Pixtral 12B is now available on Amazon SageMaker JumpStart
Today, we are excited to announce that Pixtral 12B (pixtral-12b-2409), a state-of-the-art vision language model (VLM) from Mistral AI that excels in both text-only and multimodal tasks, is available for…
Mistral-NeMo-Instruct-2407 and Mistral-NeMo-Base-2407 are now available on SageMaker JumpStart
Today, we are excited to announce that Mistral-NeMo-Base-2407 and Mistral-NeMo-Instruct-2407 large language models from Mistral AI that excel at text generation, are available for customers through Amazon SageMaker JumpStart. In…
Speed up your AI inference workloads with new NVIDIA-powered capabilities in Amazon SageMaker
At re:Invent 2024, we are excited to announce new capabilities to speed up your AI inference workloads with NVIDIA accelerated computing and software offerings on Amazon SageMaker. In this post,…
Easily deploy and manage hundreds of LoRA adapters with SageMaker efficient multi-adapter inference
The new efficient multi-adapter inference feature of Amazon SageMaker unlocks exciting possibilities for customers using fine-tuned models. This capability integrates with SageMaker inference components to allow you to deploy and…
Accelerating Mixtral MoE fine-tuning on Amazon SageMaker with QLoRA
In this post, we demonstrate how you can address the challenges of model customization being complex, time-consuming, and often expensive by using fully managed environment with Amazon SageMaker Training jobs…
Enhance speech synthesis and video generation models with RLHF using audio and video segmentation in Amazon SageMaker
In this post, we show you how to implement an audio and video segmentation solution using SageMaker Ground Truth. We guide you through deploying the necessary infrastructure using AWS CloudFormation,…
Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry
You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards, making it straightforward to manage governance information for specific model versions directly…