cronlm

cronlm

Tiny natural-language to cron model. Pluggable into @huggingface/transformers.

• Base: google/t5-efficient-tiny (~16M params)
• Shipped: INT8 ONNX (encoder + decoder + decoder-with-past), ~36 MB total
• Accuracy: 99.2% on 4 000 fresh synthetic samples · 97.3% on a hand-crafted adversarial set
• Validity: 100% of outputs are parseable 5-field cron
• Latency: ~3 ms / item on a laptop CPU

Usage

Browser / Node — transformers.js

import { pipeline } from "@huggingface/transformers";
const cron = await pipeline("text2text-generation", "pavstev/cronlm");
const out = await cron("every weekday at 9am".toLowerCase());
console.log(out[0].generated_text); // "0 9 * * 1-5"

Lowercase the input before passing — bumps accuracy on Title-Case inputs by ~2.5 pp.

Python — transformers

from transformers import pipeline
cron = pipeline("text2text-generation", model="pavstev/cronlm")
print(cron("every weekday at 9am")[0]["generated_text"])  # "0 9 * * 1-5"

Examples

Validation

A pure-Python validator/fixer is included in the cronlm package — wrap model output to catch any rare invalid generation:

from cronlm import fix
fix("0 25 * * 1")  # "0 23 * * 1"

Training

Source, dataset generator, and training scripts: https://github.com/pavstev/cronlm

License

MIT