IEEE

Impact of Transformer-Based Models in NLP: An In-Depth Study on BERT and GPT

Abstract: This article examines in depth the effects of BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pretrained Transformer) models in the field of natural ...
marktechpost

An Implementation Guide to Running NVIDIA Transformer Engine with Mixed Precision, FP8 Checks, Benchmarking, and Fallback Execution

In this tutorial, we implement an advanced, practical implementation of the NVIDIA Transformer Engine in Python, focusing on how mixed-precision acceleration can be explored in a realistic deep ...
IEEE

Redefining Deep Learning Across NLP, Image Classification and Beyond - Vision Transformers

Abstract: The self-attention technique was first used to develop transformers for natural language processing. The groundbreaking work “Attention Is All You Need” (2017) for Natural Language ...
GitHub

Automated Resume Screening and Skill Gap Analysis Using NLP

An NLP-powered recruitment automation system that utilizes Transformer-based models (BERT/S-BERT) for semantic resume screening, skill extraction, and automated skill gap analysis. The recruitment ...
GitHub

Feedback about NLP From Scratch: Classifying Names with a Character-Level RNN

I think that comment "#Cache the tensor representation of the labels" is a little confusing, especially for those who are just learning PyTorch, because you are just creating numerical representation ...
marktechpost

How to Build a Fully Functional Custom GPT-style Conversational AI Locally Using Hugging Face Transformers

In this tutorial, we build our own custom GPT-style chat system from scratch using a local Hugging Face model. We start by loading a lightweight instruction-tuned model that understands conversational ...