Zephyrnet Logo

Tag: INIT

Accelerate ML workflows with Amazon SageMaker Studio Local Mode and Docker support | Amazon Web Services

We are excited to announce two new capabilities in Amazon SageMaker Studio that will accelerate iterative development for machine learning (ML) practitioners: Local Mode...

Top News

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker | Amazon Web Services

This post is co-written with Chaoyang He, Al Nevarez and Salman Avestimehr from FedML. Many organizations are...

Introducing Terraform support for Amazon OpenSearch Ingestion | Amazon Web Services

Today, we are launching Terraform support for Amazon OpenSearch Ingestion. Terraform is an infrastructure as code (IaC) tool that helps you build, deploy, and...

Understanding Metaprogramming with Metaclasses in Python

IntroductionMetaprogramming is a fascinating aspect of software development, allowing developers to write programs that manipulate code itself, altering or generating code dynamically. This powerful...

How to Create Custom Post Type in WordPress » Rank Math

WordPress is a powerful content management system (CMS) that offers many flexibility and customization options.  However, sometimes, the default posts and pages may not meet...

How to Block IP Address in WordPress » Rank Math

Are you worried about unwanted visitors to your WordPress site? Whether it’s spam comments, malicious bots, or even determined hackers, unwanted traffic can disrupt...

Amazon SageMaker model parallel library now accelerates PyTorch FSDP workloads by up to 20% | Amazon Web Services

Large language model (LLM) training has surged in popularity over the last year with the release of several popular models such as Llama 2,...

Create a web UI to interact with LLMs using Amazon SageMaker JumpStart | Amazon Web Services

The launch of ChatGPT and rise in popularity of generative AI have captured the imagination of customers who are curious about how they can...

Mitigate hallucinations through Retrieval Augmented Generation using Pinecone vector database & Llama-2 from Amazon SageMaker JumpStart | Amazon Web Services

Despite the seemingly unstoppable adoption of LLMs across industries, they are one component of a broader technology ecosystem that is powering the new AI...

Use Amazon SageMaker Studio to build a RAG question answering solution with Llama 2, LangChain, and Pinecone for fast experimentation | Amazon Web Services

Retrieval Augmented Generation (RAG) allows you to provide a large language model (LLM) with access to data from external knowledge sources such as repositories,...

Unlock scalable analytics with AWS Glue and Google BigQuery | Amazon Web Services

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern...

Harnessing NLP Superpowers: A Step-by-Step Hugging Face Fine Tuning Tutorial

Introduction Fine-tuning a natural language processing (NLP) model entails altering the model’s hyperparameters and architecture and typically adjusting the dataset to enhance the model’s performance...

A MLOps-Enhanced Customer Churn Prediction Project

Introduction When we hear data science, the first thing that comes to mind is building a model on notebooks and training the data. But this...

Latest Intelligence

spot_img
spot_img

Chat with us

Hi there! How can I help you?