Jerry Xu on X: tab-jev: jev-like model + tabular foundation model = an in-context learner for y

tab-jev: jev-like model + tabular foundation model = an in-context learner for your text & tabular data. https://github.com/edamame-labs/tab-jev Many real industry datasets are a mix of tabular and text data: - Tabular foundation models like TabPFN learn from a few hundred labeled rows in context, with no training. But they can't read text. - Jev-style models read text and answer typed questions with scores. But they can't digest tabular data well. Experiment results on kaggle problem "Kickstarter: will the project get funded?" is shared in the repo. Missing a flight at JFK is a productivity booster... ❤️ 1 likes on X