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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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Evaluate the text summarization capabilities of LLMs for enhanced decision-making on AWS

AWS Machine Learning Blog

Calculate a ROUGE-N score You can use the following steps to calculate a ROUGE-N score: Tokenize the generated summary and the reference summary into individual words or tokens using basic tokenization methods like splitting by whitespace or natural language processing (NLP) libraries.

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Customizing coding companions for organizations

AWS Machine Learning Blog

In these two studies, commissioned by AWS, developers were asked to create a medical software application in Java that required use of their internal libraries. About the authors Qing Sun is a Senior Applied Scientist in AWS AI Labs and work on AWS CodeWhisperer, a generative AI-powered coding assistant.

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Zero-shot text classification with Amazon SageMaker JumpStart

AWS Machine Learning Blog

Natural language processing (NLP) is the field in machine learning (ML) concerned with giving computers the ability to understand text and spoken words in the same way as human beings can. Note that by following the steps in this section, you will deploy infrastructure to your AWS account that may incur costs.

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Top 10 Deep Learning Platforms in 2024

DagsHub

TensorFlow The Google Brain team created the open-source deep learning framework TensorFlow, which was made available in 2015. Libraries and Extensions: Includes torchvision for image processing, touchaudio for audio processing, and torchtext for NLP. This environment supports collaborative development and experimentation.

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Extract non-PHI data from Amazon HealthLake, reduce complexity, and increase cost efficiency with Amazon Athena and Amazon SageMaker Canvas

AWS Machine Learning Blog

AWS provides the most complete set of services for the entire end-to-end data journey for all workloads, all types of data, and all desired business outcomes. The high-level steps involved in the solution are as follows: Use AWS Step Functions to orchestrate the health data anonymization pipeline.

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Comparative Analysis: PyTorch vs TensorFlow vs Keras

Pickl AI

In industry, it powers applications in computer vision, natural language processing, and reinforcement learning. This allows users to change the network architecture on-the-fly, which is particularly useful for tasks that require variable input sizes, such as natural language processing and reinforcement learning.