How to run open-weight Nemotron 3 models on a GPU Droplet
Overview of the open-weight Nemotron 3 models: strengths, weaknesses, and how to run them on a GPU cloud servers.
Optimizing AI Models with Quanto
In this article discover Quanto a powerful quantization technique designed to optimize deep learning models without compromising the performance of the model.
Prompt-based Learning Paradigm in NLP
In this blog, we discuss various types of learning paradigms present in NLP, notations often used in the prompt-based learning paradigm, demo applications of prompt-based learning, and discuss some design considerations to make while designing a prompting environment.
I Made A New Clothing Try On App with Qwen Image Edit 2509
‘ In this tutorial, we introduce the new Qwen Image Edit 2509 clothing try on application. Follow along for instructions on using it, and an explanation on how to run it on the cloud provider. ‘
ReLU vs ELU: Picking the Right Activation for Deep Nets
Compare ReLU vs ELU activation functions in deep learning. Learn their differences, advantages, and how to choose the right one for your neural network.
Self-Learning AI Agents: A High-Level Overview
‘Learn what self-learning AI agents are, how they work, and why they matter. This overview explains core concepts, architecture, and tools in simple terms.’
StoryDiffusion
in this tutorial, we look at the new StoryDiffusion technique for generating consistent images in a series.
Trae: A New Free AI-Powered Code Editor from ByteDance
Discover Trae, a free AI-powered code editor from ByteDance featuring Builder Mode, customizable agents, Claude 3.7 access, and tool integration.
Understanding Reasoning in Large Language Models: Overview of the paper “Towards Reasoning in Large Language Models: A Survey”
In this article, we break down the paper “Towards Reasoning in Large Language Models: A Survey” in an attempt to explain relevant reasoning concepts used by LLMs.
vLLM Kubernetes: Model Loading & Caching Strategies
Learn vLLM model loading techniques on Kubernetes. Compare strategies for caching large model weights, and optimize performance for deployments.
