What is this dataset for?
Paste a Hugging Face dataset id. A small fine-tuned model reads the column names and the first row, then suggests task tags.
Suggested tags
Owner's tags:
Set by whoever uploaded the dataset, so often incomplete.
What the model reads
Column names and types, then the first row, cut to fit the model's input.
First rows
About the model
TypeSafe AI's Jev has got people excited about "System One" models: models that don't generate text, but read a state and return typed answers with probabilities that software can use directly. This page does the same thing for one narrow job. The state is a dataset's columns and first row. The answer is a set of task tags, each with a probability. The model is small enough to fine-tune yourself on Jobs and to run on a free CPU.
The tags come from GLiNER2.5-base, a 194M-parameter model from Fastino that reads a text and a list of labels together. It was fine-tuned on 16,000 Hub datasets and their owners' tags, in 17 minutes on one GPU with this training script.
On 3,000 newer datasets from owners it never saw, its first suggestion matches an owner's tag 69% of the time. That is a noisy target: owners often leave out tags that fit, and in a hand-checked sample about one dataset in ten was missing one. A suggestion that isn't in the owner's tags is not always wrong.