Haziqa Sajid

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Quantized LoRA: Fine-Tuning Large Language Models with Ease

Language models like GPT-4 have established themselves as the leading standard in the NLP industry for developing advanced applications. These models can perform diverse tasks and easily adapt to new tasks using Prompt Engineering Techniques. However, they also present a massive challenge around training and fine-tuning. Due to their massive

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Low-Rank Adaptation (LoRA): A Parameter-Efficient Fine-Tuning for LLMs

Large language models (LLMs), such as GPT-3 and LaMDA, are at the forefront of natural language processing (NLP). Trained on terabytes of text data, they generate human-like text and power multiple applications, including chatbots, virtual assistants, and search engines. This initial training process, where the LLM learns general language representations

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LLMOps Part 3: Deployment

After completing the development and validation phase, model deployment is the next important step in the LLMOps workflow. Successful deployment requires careful consideration of efficiency, scalability, and the specific needs of the deployment environment. Quantization: Optimization Technique for Efficient Deployment of LLMs Quantization is a technique used to reduce LLMs&

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LLMOps Part 2: Workflow and Model Development

Managing large language models (LLMs) through LLMOps workflows requires a structured approach to ensure effective development, deployment, and maintenance. These workflows are divided into several key phases: data collection, model development, deployment, and governance, each crucial to the performance and sustainability of LLM systems. Specific methodologies, tools, and best practices

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LLMOps Part 1: Introduction

The world is experiencing a transformative wave driven by large language models (LLMs). These advanced AI models, capable of understanding and generating human-quality text, are changing interactions with technology and information. LLMs power various applications, from chatbots and virtual assistants to content creation tools,  advanced search engines, and even personalized

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A Comprehensive Guide on AI Agents

Introduction OpenAI's mission to create artificial general intelligence (AGI) that is smarter than humans is still futuristic. However, tools like BabyAGI and AutoGPT - AI agents powered by LLMs - have already raised concerns. These AI agents use LLM's reasoning engine to plan their thinking journey

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A Comprehensive Guide to Different RAG Architectures

Introduction In an era where data doubles every two years, sifting through mountains of information to find exactly what you need can feel like searching for a needle in an ever-expanding haystack. Yet, this is the challenge that modern artificial intelligence (AI) systems, like Retrieval-Augmented Generation (RAG), are designed to