TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale, including both content understanding and generative ...

17 нояб. 2022 г. · TorchMultimodal is a PyTorch domain library for training multi-task multimodal models at scale. In the repository, we provide: Building Blocks.

TorchMultimodal is a library powered by Pytorch consisting of building blocks and end to end examples, aiming to enable and accelerate research in multimodality ...

5 февр. 2024 г. · Multimodal models are designed to process and generate information from multiple modalities, such as text, images, and possibly other forms ...

Multimodal Transformer (MulT) merges multimodal time-series via a feed-forward fusion process from multiple directional pairwise crossmodal transformers.

Продолжительность: 5:46:05
Опубликовано: 7 авг. 2024 г.

Multimodal Datasets. Multimodal datasets include more than one data modality, e.g. text + image, and can be used to train transformer-based models.

13 окт. 2021 г. · PyTorch-widedeep is an open-source deep-learning package built for multimodal problems. Widedeep was developed by Javier Rodriguez Zaurin.

31 мар. 2024 г. · PyTorch Frame makes tabular deep learning easy by providing a PyTorch-based data structure to handle complex tabular data.

21 нояб. 2022 г. · In this blog, we present a case study demonstrating the scaling of FLAVA to 10B params using techniques from PyTorch Distributed.