6 datasets found

A dataset of 20 million unlabeled URLs for pre-training

Point-BERT is a new paradigm for learning point cloud Transformers. It pre-trains standard point cloud Transformers with a Masked Point Modeling (MPM) task.

The dataset used for training and testing the proposed Cross-View Language Modeling framework.

The dataset used in this paper is a pre-trained BERT model trained on English Wikipedia and Books datasets.

A dataset of 70000 handwritten samples of Bengali numerals for recognition using artificial neural network based architecture pre-trained by a stacked denoising autoencoder.

This paper proposes BERT, a pre-trained deep bidirectional transformer for language understanding.