Fine-Tuning

Build a LoRA Fine-Tuning & Inference Engine in Pure PyTorch

A hands-on build guide for a LoRA fine-tuning and inference engine featuring low-rank adapter gradients, fused weight updates, and runtime adapter swapping in pure PyTorch.

A diagram of a transformer with LoRA adapters

Building a Pure-Python LoRA Adapter for BERT: A Portfolio Project

This post walks through building a LoRA adapter injection layer for BERT in pure Python, including a complete fine-tuning loop, and shows how to extend it for production-grade systems.

Short description of the cover image subject.

Hands‑On Build Guide: LoRA‑Based LLM Fine‑Tuning for Your Portfolio CV

A hands‑on guide to building a LoRA‑based LLM fine‑tuning system you can ship to GitHub and discuss in interviews.

Low-rank adaptation diagram showing decomposed weight matrices added to a transformer layer

Build a LoRA Adapter from Scratch: A Portfolio-Ready PyTorch Project

A hands-on build guide for implementing a LoRA adapter from scratch in PyTorch, including rank-decomposed weight matrices and a complete fine-tuning loop for BERT — designed to signal real ML engineering skill on a portfolio.

Terminal screenshot of a fine-tuning training run showing loss curves.

Fine-Tuning a Small LLM: A Hands-On Experiment

A working engineer’s journal of fine-tuning a small open-source LLM with LoRA on a custom dataset — the full pipeline, the surprises, and the measurable results.