TokenTown: A visual way to understand how LLMs work

laurentiurad

You can paste text and immediately see how it's split into tokens, along with token IDs, counts, and other details. It's useful for understanding why prompts cost what they do, why context limits behave the way they do, and why models sometimes split words in unexpected places. I made it because I kept explaining tokenization to friends and realized there wasn't a simple, interactive tool that focused on learning rather than documentation. I'd love feedback on: Features that would make it more useful UI improvements Bugs or edge cases you've found Hope it's useful!

lionel-messi

this doesnt help at all

Hugada

I think you need to know a lot to understand this, so perhaps it should mention what you should already know in order for it to be comprehensible.

onlyrealcuzzo

This would be really cool if it did 3Brown 1Blue's style of visualization - but interactively, and allowed you to explore at any stage.

foltik

I read through the explanations and they’re all typical hand wavy LLM prose, full of jargon, and random tangential details. If you’re going to publicly present this as a learning tool, it would be great if you spent some actual human brain cycles writing and polishing it by hand, rather than just chucking the first thing that claude spits out over the fence. I can pretty much guess the prompt you used and probably get the same thing.

hk__2

Can we filter out random vibe-coded projects like this from the homepage?

simpledevraf

interesting approach to describe this topic

markstos

From this I learned LLMs are complex and compute-intensive.

GCUMstlyHarmls

"This is not a loop in code: it is a stack of distinct blocks" Proceeds to literally loop around 6 times.

arcs-

I'd appreciate if you could make this mobile ready, with llms I expect this to be very easy

phikappa

I'd suggest the LLM visualiser (1) by Brendan Bycroft. I'm a visual learner and it helped me understand LLMs better than anything else ever could. (1) https://bbycroft.net/llm