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Tag: Docker Container

Build protein folding workflows to accelerate drug discovery on Amazon SageMaker | Amazon Web Services

Drug development is a complex and long process that involves screening thousands of drug candidates and using computational or experimental methods to evaluate leads....

How Patsnap used GPT-2 inference on Amazon SageMaker with low latency and cost | Amazon Web Services

This blog post was co-authored, and includes an introduction, by Zilong Bai, senior natural language processing engineer at Patsnap. You’re likely familiar with the...

Optimize AWS Inferentia utilization with FastAPI and PyTorch models on Amazon EC2 Inf1 & Inf2 instances | Amazon Web Services

When deploying Deep Learning models at scale, it is crucial to effectively utilize the underlying hardware to maximize performance and cost benefits. For production...

SSH Servers Hit in ‘Proxyjacking’ Cyberattacks

Threat actors are exploiting vulnerable secure shell protocol (SSH) servers to launch Docker services that take advantage of an emerging and lucrative attack vector...

Auto-labeling module for deep learning-based Advanced Driver Assistance Systems on AWS | Amazon Web Services

In computer vision (CV), adding tags to identify objects of interest or bounding boxes to locate the objects is called labeling. It’s one of...

Build high-performance ML models using PyTorch 2.0 on AWS – Part 1 | Amazon Web Services

PyTorch is a machine learning (ML) framework that is widely used by AWS customers for a variety of applications, such as computer vision, natural...

Implement a multi-object tracking solution on a custom dataset with Amazon SageMaker | Amazon Web Services

The demand for multi-object tracking (MOT) in video analysis has increased significantly in many industries, such as live sports, manufacturing, and traffic monitoring. For...

Perform batch transforms with Amazon SageMaker Jumpstart Text2Text Generation large language models | Amazon Web Services

Today we are excited to announce that you can now perform batch transforms with Amazon SageMaker JumpStart large language models (LLMs) for Text2Text Generation....

GPT-NeoXT-Chat-Base-20B foundation model for chatbot applications is now available on Amazon SageMaker | Amazon Web Services

Today we are excited to announce that Together Computer’s GPT-NeoXT-Chat-Base-20B language foundation model is available for customers using Amazon SageMaker JumpStart. GPT-NeoXT-Chat-Base-20B is an...

Securing MLflow in AWS: Fine-grained access control with AWS native services

With Amazon SageMaker, you can manage the whole end-to-end machine learning (ML) lifecycle. It offers many native capabilities to help manage ML workflows aspects,...

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

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the...

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

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the...

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