What Hollerith is
Hollerith is a transformer pretrained to predict directly from tables, trained and served by Monarcha. It reads your labeled table at prediction time rather than learning from it.fit computes no gradients. It hands the model your table, and predict scores new rows
against it.
The name is Herman Hollerith, whose punch card carried the 1890 census and made the first
machine-readable table.
What that gets you
- A result before you build a pipeline. Point it at a labeled table and predict. You find out whether the signal is there before you spend the week on feature engineering.
- One endpoint instead of many models. You keep one call where you would otherwise keep a trained model per table, per segment or per customer.
- Nothing to tune. There is no learning rate, no tree depth, no search space and no retraining schedule.
What it costs
- Your table is read on every call. Its size is a cost you pay each time rather than once.
fitis a real job on a GPU. It takes seconds to minutes and bills the rows you send.- Column names carry no meaning. Text and dates are read as categories, so the model sees which rows share a value, not what the value means.
Where to start
- Quickstart — install, key, and a first prediction
- How Hollerith works — why reading a table beats training on it
- The model — what it is good at, and where it is not the right tool
- Improving accuracy — what to try when the first number disappoints