Remove 2009 Remove AWS Remove Deep Learning
article thumbnail

Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

AWS Machine Learning Blog

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. M tokens/$) trained such models with AWS Trainium without losing any model quality. We’ll outline how we cost-effectively (3.2 billion in Pythia.

AWS 131
article thumbnail

Fast and cost-effective LLaMA 2 fine-tuning with AWS Trainium

AWS Machine Learning Blog

In this post, we walk through how to fine-tune Llama 2 on AWS Trainium , a purpose-built accelerator for LLM training, to reduce training times and costs. We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw.

AWS 132
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Top 10 Generative AI Companies Revealed

Towards AI

Amazon (AWS) 👉Industry domain: Online retail and web services provider 👉Location: Over 175 Amazon fulfillment centers globally 👉Year founded: 1994 👉Key Products developed: Amazon Bedrock, Q, Code Whisperer, Sage Maker 👉Benefits: Fully managed generative AI service options, AWS free tier for experimentation 7.

AI 110
article thumbnail

Top recommended AI companies in Vietnam to collaborate in 2024

Dataconomy

KMS Technology KMS Technology is a pioneer in the AI sector in Vietnam, providing businesses with robust AI and machine learning solutions. Since its inception in 2009, KMS Technology has remained committed to delivering top-notch services in AI, data analytics, and software development.

AI 113
article thumbnail

Financial text generation using a domain-adapted fine-tuned large language model in Amazon SageMaker JumpStart

AWS Machine Learning Blog

One of the major challenges in training and deploying LLMs with billions of parameters is their size, which can make it difficult to fit them into single GPUs, the hardware commonly used for deep learning. On August 21, 2009, the Company filed a Form 10-Q for the quarter ended December 31, 2008.

ML 88
article thumbnail

Amazon SageMaker built-in LightGBM now offers distributed training using Dask

AWS Machine Learning Blog

For the NYC taxi data, we use the yellow trip taxi records from 2009–2022. He focuses on developing scalable machine learning algorithms. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering.

Algorithm 108
article thumbnail

Domain-adaptation Fine-tuning of Foundation Models in Amazon SageMaker JumpStart on Financial data

AWS Machine Learning Blog

One of the major challenges in training and deploying LLMs with billions of parameters is their size, which can make it difficult to fit them into single GPUs, the hardware commonly used for deep learning. On August 21, 2009, the Company filed a Form 10-Q for the quarter ended December 31, 2008.

ML 52