In today’s data-driven world, having access to powerful computing resources is essential for developers, data scientists, and students alike. Enter Google Colab – a game-changing platform that provides free access to cloud computing resources, including GPU support, without requiring any local setup. Whether you’re a beginner taking your first steps in Python programming or an… →

Proteins are the essential component behind nearly all biological processes, from catalyzing reactions to transmitting signals within cells. While advances like AlphaFold have transformed our ability to predict static protein structures, a fundamental challenge remains: understanding the dynamic behavior of proteins. Proteins naturally exist as ensembles of interchanging conformations that underpin their function. Traditional experimental… →

In this tutorial, we will build an efficient Legal AI CHatbot using open-source tools. It provides a step-by-step guide to creating a chatbot using bigscience/T0pp LLM, Hugging Face Transformers, and PyTorch. We will walk you through setting up the model, optimizing performance using PyTorch, and ensuring an efficient and accessible AI-powered legal assistant. Copy CodeCopiedUse… →

Large Language Models (LLMs) face significant challenges in optimizing their post-training methods, particularly in balancing Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) approaches. While SFT uses direct instruction-response pairs and RL methods like RLHF use preference-based learning, the optimal allocation of limited training resources between these approaches remains unclear. Recent studies have shown that models… →

The development of high-performing machine learning models remains a time-consuming and resource-intensive process. Engineers and researchers spend significant time fine-tuning models, optimizing hyperparameters, and iterating through various architectures to achieve the best results. This manual process demands computational power and relies heavily on domain expertise. Efforts to automate these aspects have led to the development… →

In today’s digital landscape, technology continues to advance at a steady pace. One development that has steadily gained attention is the concept of the AI agent—software designed to perform tasks autonomously by understanding and interacting with its environment. This article offers a measured exploration of AI agents, examining their definition, evolution, types, real-world applications, and… →

Training large language models (LLMs) has become central to advancing artificial intelligence, yet it is not without its challenges. As model sizes and datasets continue to grow, traditional optimization methods—most notably AdamW—begin to show their limitations. One of the main difficulties is managing the computational cost and ensuring stability throughout extended training runs. Issues such… →

In this tutorial, we explore how to fine-tune NVIDIA’s NV-Embed-v1 model on the Amazon Polarity dataset using LoRA (Low-Rank Adaptation) with PEFT (Parameter-Efficient Fine-Tuning) from Hugging Face. By leveraging LoRA, we efficiently adapt the model without modifying all its parameters, making fine-tuning feasible on low-VRAM GPUs.Steps to the implementation in this tutorial can be broken… →