Feb 27, 2025 · Transformers have redefined deep learning across NLP, computer vision, and beyond. With advancements like BERT, GPT and Vision Transformers (ViTs) they continue to push the boundaries of AI and language understanding and multimodal learning.

Mar 26, 2025 · 7. Transformer Model. This block defines the main Transformer class which combines the encoder and decoder layers. It also includes the embedding layers and the final output layer. self.encoder_embedding = nn.Embedding(src_vocab_size, d_model): Initializes the embedding layer for the source sequence, mapping tokens to continuous vectors of size ...

Apr 10, 2025 · This comprehensive, hands-on tutorial teaches you how to simplify deep learning model development with PyTorch Lightning. Perfect for beginners and experienced developers alike, it covers environment setup, model training, and practical examples.

Mar 29, 2025 · Transformer is a deep learning architecture that is very popular in natural language processing (NLP) tasks. It is a type of neural network that is designed to process sequential data, such as text. In this article, we will explore the concept of attention and the transformer architecture. Specifically, you will learn: What problems …

In this tutorial, you will learn to implement a transformer-based language model from scratch. You’ll cover data preparation, model architecture, training, and evaluation. By the end, you’ll be able to build, train, and use your own transformer model for text generation and related tasks.

Emphasizing practical applications, the course includes hands-on coding exercises. Instructor Fred Nwanganga explains what sequence data is, common sequence data problems, recurrent neural networks and its variants, transformers, and how to solve several types of sequence data problems using pre-trained transformer models in Python. Learn More

The goal of this project is to have a deep understanding of deep learning concepts implementing a Transformer model from scratch using PyTorch. The Transformer, introduced in the groundbreaking paper "Attention Is All You Need", revolutionized sequence modeling, especially in natural language processing (NLP) tasks like machine translation.

Feb 6, 2025 · At its core, a Transformer is built on the self-attention mechanism. Think of it as Aryan reading a sentence and instinctively focusing on key words based on context, rather than processing...

In this course, you will learn how to apply deep learning models to Natural Language Processing (NLP) tasks using Python. By the end of the course, you will be able to understand and implement cutting-edge deep learning models, including Feedforward Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks, tailored for NLP applications.

Aug 13, 2024 · What is a Transformer Model? A Transformer is a popular and powerful deep-learning architecture used in natural language processing (NLP). It’s particularly effective for tasks like language translation, text summarization, and question-answering.