. ├── README.md ├── main.py # Main training script ├── transformer.py # Transformer model implementations ├── dataset.py # Dataset classes for both tasks ├── tokenizer.py # Simple word-level tokenizer ...

This paper investigates the diffusion characteristics of dissolved gases in a ±400kV converter transformer under various fault types and analyzes the temporal changes in gas concentration at different ...

We employ PointNet++ for feature extraction and utilize a Transformer encoder module to process spatial contextual information, thereby constructing a comprehensive representation of the robot’s ...

阿里妹导读本文希望围绕“Transformer到底是解决什么问题的”这个角度，阐述NLP发展以来遇到的关键问题和解法，通过这些问题引出Transformer实现原理，帮助初学者理解。近期小组内发起AI技术的学习分享，单看 ...

Let’s hear how the new Belief State Transformer architecture unlocks new abilities by combining a standard GPT-style architecture of a forward encoder for token prediction with an additional backward ...

Originally introduced in a 2017 paper, “Attention Is All You Need” from researchers at Google, the transformer was introduced as an encoder-decoder architecture specifically designed for ...

Fix loading of LeViT safetensor weights, remove conversion code which should have been deactivated Add 'SO150M' ViT weights trained with SBB recipes, decent results, but not optimal shape for ImageNet ...

The Transformer design includes an encoder-decoder structure, however in the context of ASD identification, we concentrate on the encoder. The Transformer encoder’s main components include ...