May 4, 2026
Small model, huge comment energy
Train Your Own LLM from Scratch
The internet is obsessed with building a baby chatbot on a laptop — and arguing if that even counts as “large”
TLDR: This workshop shows people how to build a tiny text-writing AI themselves on a laptop, making a complicated topic feel surprisingly doable. Commenters loved the beginner-friendly idea, but also sparked a petty-fun debate over whether calling it an “LLM” is overselling something this small.
A new workshop is promising a very seductive tech fantasy: build your own ChatGPT-style text generator from scratch on a regular laptop in under an hour, with no mystery shortcuts and no copy-paste magic. The idea is simple enough for curious coders: you write every piece yourself, from turning words into numbers to training the model to spit out Shakespeare-ish lines. And the community reaction? A mix of “finally, something approachable!” and “okay, but let’s not get carried away.”
The warmest takes came from people thrilled to see artificial intelligence explained in a hands-on, human way. One commenter called it a great first step, basically cheering for a beginner-friendly on-ramp instead of the usual impossible-to-follow wizardry. But of course, this is the internet, so the praise immediately got side-eyed by the realism police. The snarkiest comment bluntly rewrote the title as “Train your LM from scratch,” with a jab that most people don’t own a machine big enough to make it truly “large.” Ouch. That tiny wording fight became the thread’s main mini-drama: is this an inspiring learning tool, or a slightly cheeky overpromise?
Then came the classic comment-section chaos. One person dropped a Stanford course recommendation like an academic mic drop, basically saying: nice starter pack, but here’s the deep end. Another asked the practical question everyone was thinking: how far can this actually scale on one machine? And the funniest response of all dodged the topic entirely: “Been doing it since the day I was born,” turning “training a language model” into a joke about learning to talk. In other words, the project may be about code, but the real show is the crowd: hopeful beginners, nitpickers, prestige-name droppers, and one very proud baby genius.
Key Points
- •The article presents a hands-on workshop for building a GPT-style language model training pipeline entirely from scratch without black-box model-loading libraries.
- •The workshop is scaled down from nanoGPT and targets a roughly 10 million-parameter model that can train on a laptop in under an hour.
- •Participants implement four core components themselves: tokenization, transformer architecture, training loop, and text generation.
- •The workshop supports local and cloud execution, including Apple Silicon via MPS, NVIDIA GPUs via CUDA, CPU, and Google Colab.
- •Three model sizes are provided—Tiny, Small, and Medium—with all configurations using character-level tokenization, vocab_size=65, and block_size=256.