Google AI 发布 TabFM:混合注意力表格基座模型,支持零样本分类与回归

Google AI Introduces TabFM: A Hybrid-Attention Tabular Foundation Model for Zero-Shot Classification and Regression

精选理由

Google 新出的 TabFM 模型,不用任何训练就能直接搞定表格数据的分类和回归,一次前向传播出结果,省心省力。

AI 摘要

Google Research 推出了 TabFM,一个基于混合注意力机制的表格基座模型。它能够在零样本设置下完成分类与回归任务,通过上下文学习实现单次前向传播预测。该模型无需对每个新数据集进行训练、超参数调整或特征工程。TabFM 为表格数据场景提供了即开即用的预测能力。

图片来源 · marktechpost
原文 · marktechpost

Google AI Introduces TabFM: A Hybrid-Attention Tabular Foundation Model for Zero-Shot Classification and Regression

Google Research has released TabFM, a foundation model for tabular data. It performs zero-shot classification and regression through in-context learning. Predictions come from a single forward pass, with no per-dataset training, hyperparameter tuning, or feature engineering. The post Google AI Introduces TabFM: A Hybrid-Attention Tabular Foundation Model for Zero-Shot Classification and Regression appeared first on MarkTechPost .