AWS Machine Learning Blog

OCTOBER 5, 2023

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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Towards AI

APRIL 19, 2024

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.

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

Now you can also fine-tune 7 billion, 13 billion, and 70 billion parameters Llama 2 text generation models on SageMaker JumpStart using the Amazon SageMaker Studio UI with a few clicks or using the SageMaker Python SDK. The model is deployed in an AWS secure environment and under your VPC controls, helping ensure data security.

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AWS Machine Learning Blog

JANUARY 30, 2023

They’re available through the SageMaker Python SDK. Dask is an open-source parallel computing library that allows for distributed parallel processing of large datasets in Python. It’s designed to work with the existing Python and data science ecosystem such as NumPy and Pandas. 1 5329 5414 0.937 0.947 65.6 2 3175 3294 0.94

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AWS Machine Learning Blog

APRIL 18, 2023

Solution overview In the following sections, we provide a step-by-step demonstration for fine-tuning an LLM for text generation tasks via both the JumpStart Studio UI and Python SDK. On August 21, 2009, the Company filed a Form 10-Q for the quarter ended December 31, 2008. per diluted share, compared to $5,716,000, or $0.33

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AWS Machine Learning Blog

APRIL 18, 2023

Solution overview In the following sections, we provide a step-by-step demonstration for fine-tuning an LLM for text generation tasks via both the JumpStart Studio UI and Python SDK. On August 21, 2009, the Company filed a Form 10-Q for the quarter ended December 31, 2008. per diluted share, compared to $5,716,000, or $0.33

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AWS Machine Learning Blog

NOVEMBER 11, 2024

Prerequisites To try out this solution using SageMaker JumpStart, you’ll need the following prerequisites: An AWS account that will contain all of your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker. We then also cover how to fine-tune the model using SageMaker Python SDK.

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