We break down the Encoder architecture in Transformers, layer by layer! If you've ever wondered how models like BERT and GPT process text, this is your ultimate guide. We look at the entire design of ...

Vision-language models (VLMs) are rapidly changing how humans and robots work together, opening a path toward factories where machines can “see,” ...

In this video, we break down BERT (Bidirectional Encoder Representations from Transformers) in the simplest way possible—no ...

Hi, and thanks for the great work on this project! I'm currently working with the training code and noticed something potentially inconsistent. While the documentation and flags suggest support for ...

Large language models (LLMs) have become central tools in writing, coding, and problem-solving, yet their rapidly expanding use raises new ethical ...

Encoder models like BERT and RoBERTa have long been cornerstones of natural language processing (NLP), powering tasks such as text classification, retrieval, and toxicity detection. However, while ...

1 School of Media & Communication Shanghai Jiao Tong University, Shanghai, China 2 Department of Critical Care Medicine, Sir Run Run Shaw Hospital, Hangzhou, Zhejiang, China Objective: This study ...

Abstract: Recently Bidirectional Encoder Representations from Transformers (BERT) model has gained lots of attention because of its state-of-the-art performance in multiple natu-ral language ...

Thanks for your great project. You use a BERT encoder instead of a CLIP encoder for text. Is there any specific reason for the choice? Thanks Sign up for free to join this conversation on GitHub.