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

AWS Machine Learning Blog

Our high-level training procedure is as follows: for our training environment, we use a multi-instance cluster managed by the SLURM system for distributed training and scheduling under the NeMo framework. He was a recipient of the NSF Faculty Early Career Development Award in 2009. Youngsuk Park is a Sr. He founded StylingAI Inc.,

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

AWS Machine Learning Blog

In these cases, you might be able to speed up the process by distributing training over multiple machines or processes in a cluster. This post discusses how SageMaker LightGBM helps you set up and launch distributed training, without the expense and difficulty of directly managing your training clusters. 2 3175 3294 0.94

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

AWS Machine Learning Blog

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

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

AWS Machine Learning Blog

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

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