Unlock cost-effective AI inference using Amazon Bedrock's serverless capabilities with a trained model in Amazon SageMaker
In this post, I'll show you how to use amazon Bedrock, with its fully managed on-demand API, with your trained ...
In this post, I'll show you how to use amazon Bedrock, with its fully managed on-demand API, with your trained ...
Large language models (LLMs) have become an integral part of modern ai applications, powering tools like chatbots and code generators. ...
OPINIONAnd how to start using Python.Can training programs generate more economic prosperity? Image generated with Leonardo aiMuch of contemporary data ...
Accelerating LLM inference is an important ML research problem, since generating autoregressive tokens is computationally expensive and relatively slow, and ...
LLMs are driving important advances in research and development today. There has been a significant shift in research objectives and ...
Implementation of speculative and contrastive decodingLarge language models are composed of billions of parameters (weights). For each word it generates, ...
Medprompt, a runtime steering strategy, demonstrates the potential to guide general-purpose LLMs to achieve cutting-edge performance in specialized domains such ...
Today at AWS re:Invent 2024, we are excited to announce a new feature for amazon SageMaker inference endpoints: the ability ...
This post is co-written with Abhishek Sawarkar, Eliuth Triana, Jiahong Liu and Kshitiz Gupta from NVIDIA. At re:Invent 2024, we ...
The new efficient multi-adapter inference feature of amazon SageMaker unlocks exciting possibilities for customers using fine-tuned models. This capability integrates ...