Embracing the Generative AI Revolution: NVIDIA’s Dominance and Future Prospects Introduction: In the ever-evolving landscape of information technology, a pivotal moment has arrived. As declared by Nvidia CEO Jensen Huang, a new era of computing is upon us, driven by the convergence of accelerated computing and generative AI. In this blog post, we delve into … Read more
Tokenization and Subword Encoding: Output: Handling Special Tokens and Padding: Output: Data Cleaning and Normalization Techniques: Output: These sample codes show how to use HuggingFace’s Tokenizers library and regular expressions to accomplish tokenization, subword encoding, managing special tokens and padding, as well as data cleaning and normalization procedures. Based on your unique NLP goals and … Read more
Understanding the Transformer Architecture: Self-Attention Mechanism: Transformer Layers and Multi-Head Attention: Positional Encoding: Sample Code Example (using Python and PyTorch): This example program uses PyTorch to demonstrate a condensed version of a Transformer model. It comprises the key elements covered, including positional encoding, the Transformer layer, and multi-head attention. Keep in mind that there are … Read more
Introduction to Natural Language Processing An overview of natural language processing (NLP) and its uses will be given in this section. We will also go over some fundamental ideas and terms that are used in the industry. We’ll also provide sample code to get you started using Transformers for NLP. Overview of NLP: A branch … Read more
Attention Viz: A Tool for Visualizing Self-Attention in Transformers An increasingly common neural network design for natural language processing (NLP) tasks is the transformer. The employment of self-attention by transformers, a process that enables the model to pay attention to various elements of the input sequence, is one of their distinguishing characteristics. When doing tasks … Read more