TinyTitle

A tiny model (~1.8M params) that turns a chat message into a short title (2-10 words). English only. The whole thing (model + tokenizer + runtime) runs in under 5 MiB of ram, in a few tens of ms, on one small C binary.

It's a small GRU with a copy trick: for each title word it either makes up a word from its 8k vocabulary or copies a whole word straight from your message (so it keeps your spelling and casing).

Honest note: an LLM wrote almost all of this while I nodded along. It works tho. It's a toy, not a real llm.

quickstart

This is a custom format (.ttm1) with a custom C runtime, so it does not work with transformers or llama.cpp. You need the runtime source from the github repo.

# build the runtime (needs cc, nothing else)
cc -std=c11 -O3 -DNDEBUG -o title-v1 runtime/main.c -lm

# run it
./title-v1 model.ttm1 "Why does my wifi keep dropping?"

Files in this repo:

• model.ttm1 - the int8 model (1.98 MB)
• tokenizer-8k.json + tok-8k.ttok - the tokenizer
• runtime/ - main.c, ttm.h, Makefile (the whole runtime is just those files)

numbers

metric	value
params	~1.8M (int8)
model file	1.98 MB
peak rss	4.89 mib (all pages touched)
typical cpu	~25 ms
vocab	8k unigram

train

Training needs python + torch. Full instructions in the github repo. It trains in under 0.5 GB of vram.

license

MIT. Training data comes from three public huggingface datasets (SupraLabs/chat-titles-filtered-115K cc-by-4.0, ogrnz/chat-titles MIT, Michionlion/chat-titles-english cc-by-4.0), assembled by the github repo's build_dataset.py.