From Quantization to Inference: Beginners Guide for Practical Finetuning
A beginner-friendly guide that bridges the gap between quantization and inference, providing practical insights into fine-tuning techniques.
Building GPT from First Principles: Code and Intuition
An intuitive and code-driven exploration of building GPT models from scratch, unraveling the principles behind their architecture.
Understanding Quantization in Deep Learning
A comprehensive guide to memory optimization in deep learning, focusing on quantization techniques and their practical implementation in modern neural networks.
A Guide to Fine-tuning Methods in LLMs (Part 1)
A deep dive into modern fine-tuning techniques for Large Language Models, exploring methods like LoRA, QLoRA, and their practical implementations.