Category:Machine Learning

Turning meaning into a list of numbers

Building Blocks · Part 2

Part 1 gave you the dials. This one gives them something to act on.

The billions of knobs inside a model

Building Blocks · Part 1

Every model you've ever used is, underneath, a very long list of numbers. Here's why that turned out to be the winning design.

Twelve Pieces, One Working Model

Building Blocks · Part 0

Somewhere between "it's just predicting the next word" and a hundred-billion-dollar training run sits an actual mechanism.

Optimizing a Model: The Complete Guide to Distillation, Quantization, Pruning, and Beyond

Training a capable model is only half the battle. The model that comes out of pretraining or fine-tuning is almost never the model you actually want to ship.

Below Four Bits: QAT, BitNet, and the Race Toward One-Bit Intelligence

Quantization · Part 4

Everything in this series so far has been post-training quantization: take a finished model, compress it, hope the damage is small.

GGUF and the Art of Choosing a Quant: A Field Guide to Local Models

Quantization · Part 3

Open any popular model's page on Hugging Face and you'll find the GGUF listings: Q4KM, Q5KS, Q6K, Q80, IQ2XS — a wall of cryptic suffixes, each a different point on a size-quality curve, downloaded millions of times by people running models on gaming PCs an…

The Outlier Problem: The Discovery That Shaped Modern Quantization

Quantization · Part 2

Here's a puzzle that stumped the field around 2022. Quantization recipes that worked beautifully on small language models — clean INT8, minimal quality loss — fell off a cliff on big ones.

Quantization From the Bits Up: How 4-Bit Models Actually Work

Quantization · Part 1

Every series I've written so far has bumped into quantization from the side — QLoRA compressing frozen bases, the optimization guide's memory math, GGUF files on Hugging Face with cryptic suffixes.

Life After Training: Merging LoRAs, Stacking Them, and Serving a Hundred Fine-Tunes on One GPU

LoRA Deep Dive · Part 4

The first three articles in this series were about making an adapter. This one is about what makes adapters a genuinely different kind of artifact from a fine-tuned model: what you can do with them afterward.