Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In the process...
In the world of software development, code review and approval are important processes for ensuring the quality, security, and functionality of the software being...
Today, we are excited to announce that Code Llama foundation models, developed by Meta, are available for customers through Amazon SageMaker JumpStart to deploy...
When deploying a large language model (LLM), machine learning (ML) practitioners typically care about two measurements for model serving performance: latency, defined by the...
OpenAI Whisper is an advanced automatic speech recognition (ASR) model with an MIT license. ASR technology finds utility in transcription services, voice assistants, and...
In this post, we showcase fine-tuning a Llama 2 model using a Parameter-Efficient Fine-Tuning (PEFT) method and deploy the fine-tuned model on AWS Inferentia2....
Introduction to DeFi’s Significance in Crypto Anatoly Yakovenko, a co-founder of Solana (SOL), has recently shed light on what he considers the most significant...
Today, Amazon SageMaker launches a new version (0.25.0) of Large Model Inference (LMI) Deep Learning Containers (DLCs) and adds support for NVIDIA’s TensorRT-LLM Library....
Generative artificial intelligence (generative AI) models have demonstrated impressive capabilities in generating high-quality text, images, and other content. However, these models require massive amounts...
This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. This is the third post in a series discussing the integration...