Transformers

A brand new solution to increase the capabilities of huge language models

Most languages use word position and sentence structure to extract meaning. For...

How Relevance Models Foreshadowed Transformers for NLP

— that he saw further only by standing on the shoulders of giants — captures a timeless truth about science. Every breakthrough rests on countless layers of prior progress, until someday … all...

When Transformers Sing: Adapting SpectralKD for Text-Based Knowledge Distillation

While working on my Knowledge Distillation problem for intent classification, I faced a puzzling roadblock. My setup involved a teacher model, which is RoBERTa-large (finetuned on my intent classification), and a student model, which...

Scaling Recommender Transformers to a Billion Parameters

! My name is Kirill Khrylchenko, and I lead the RecSys R&D team at Yandex. One in all our goals is to develop transformer technologies inside the context of recommender systems, an objective we’ve...

An Interactive Guide to 4 Fundamental Computer Vision Tasks Using Transformers

and Vision Model? Computer Vision is a subdomain in artificial intelligence with a big selection of applications specializing in image processing and understanding. Traditionally addressed through Convolutional Neural Networks (CNNs), this field has been...

Learn How one can Use Transformers with HuggingFace and SpaCy

Introduction the the state-of-the-art architecture for NLP and never only. Modern models like ChatGPT, Llama, and Gemma are based on this architecture introduced in 2017 within the Attention Is All You Need paper from...

The unique, mathematical shortcuts language models use to predict dynamic scenarios

Let’s say you’re reading a story, or playing a game of chess....

Audio Spectrogram Transformers Beyond the Lab

Need to know what draws me to soundscape evaluation? It’s a field that mixes science, creativity, and exploration in a way few others do. Initially, your laboratory is wherever your feet take you — a forest trail,...

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