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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.

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Bundesliga Match Facts Shot Speed – Who fires the hardest shots in the Bundesliga?

AWS Machine Learning Blog

His 2009 strike against Leverkusen at a speed of 125 km/h is one that is vividly remembered because the sheer velocity of Hitzlsperger’s free-kick was enough to leave Germany’s number one goalkeeper, René Adler, seemingly petrified. To achieve this, our process uses a synchronization algorithm that is trained on a labeled dataset.

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Top recommended AI companies in Vietnam to collaborate in 2024

Dataconomy

Since its inception in 2009, KMS Technology has remained committed to delivering top-notch services in AI, data analytics, and software development. Their team of AI experts excels in creating algorithms for deep learning, predictive analytics, and automation.

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Mastering digital transformation strategy: A comprehensive guide for success

Data Science Dojo

In 2009, Uber came along and revolutionized the entire taxi business. A common pitfall for businesses undergoing digital transformation is assuming that it is easy to migrate existing technology to a new platform or system (like the cloud or AWS). And it’s not just the flashy firms in Silicon Valley that are feeling the pinch.

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

AWS Machine Learning Blog

Amazon SageMaker provides a suite of built-in algorithms , pre-trained models , and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning.

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Fine-tune Llama 2 for text generation on Amazon SageMaker JumpStart

AWS Machine Learning Blog

You can easily try out these models and use them with SageMaker JumpStart, which is a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. The model is deployed in an AWS secure environment and under your VPC controls, helping ensure data security. Default is 5.

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

AWS Machine Learning Blog

To make things easy, these three inputs depend solely on the model name, version (for a list of the available models, see Built-in Algorithms with pre-trained Model Table ), and the type of instance you want to train on. learning_rate – Controls the step size or learning rate of the optimization algorithm during training.

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