Summarization has become a very helpful way of tackling the issue of data overburden. In my earlier story, I shared how you can create your personal text summarizer using the extractive method — if you have tried that, you may have noticed that, because no new sentences were generated from the original content, at times you may have difficulties understanding the generated … [Read more...] about The Secret Guide To Human-Like Text Summarization
Natural Language Processing
In recent years there has been an explosion of methods based on self-attention and in particular Transformers, first in the field of Natural Language Processing and recently also in the field of Computer Vision.If you don’t know what Transformers are, or if you want to know more about the mechanism of self-attention, I suggest you have a look at my first article on this … [Read more...] about Is Attention What You Really Need In Transformers?
Transformers are a very powerful Deep Learning model that has been able to become a standard in many Natural Language Processing tasks and is poised to revolutionize the field of Computer Vision as well.It all began in 2017 when Google Brain published the paper destined to change everything, Attention Is All You Need . Researchers apply this new architecture to … [Read more...] about On Transformers, TimeSformers, And Attention
This research summary is part of our AI for Marketing series which covers the latest AI & machine learning approaches to 5 aspects of marketing automation:AttributionOptimizationPersonalizationAnalyticsContent Generation: ImagesContent Generation: VideosContent Generation: TextCan AI help you write high converting copy for your advertising and marketing … [Read more...] about AI Approaches For Text Generation In Marketing & Advertising Use Cases
In this article, we will learn about …… the difference between extractive and abstractive text summarization.… what the ROUGE score is.… why and where it fails.Text SummarizationWe refer to text summarization as the process of training an Artificial Intelligence (AI) model to produce a smaller chunk of text out of a bigger chunk of text. Where “smaller … [Read more...] about To ROUGE Or Not To ROUGE?
The introduction of transfer learning and pretrained language models in natural language processing (NLP) pushed forward the limits of language understanding and generation. Transfer learning and applying transformers to different downstream NLP tasks have become the main trend of the latest research advances.At the same time, there is a controversy in the NLP community … [Read more...] about 10 Leading Language Models For NLP In 2021
I created this notebook to better understand the inner workings of Bert. I followed a lot of tutorials to try to understand the architecture, but I was never able to really understand what was happening under the hood. For me it always helps to see the actual code instead of just simple abstract diagrams that a lot of times don’t match the actual implementation. If you’re like … [Read more...] about BERT Inner Workings
This notebook is used to fine-tune GPT2 model for text classification using Hugging Face transformers library on a custom dataset.Hugging Face is very nice to us to include all the functionality needed for GPT2 to be used in classification tasks. Thank you Hugging Face!I wasn’t able to find much information on how to use GPT2 for classification so I … [Read more...] about GPT2 For Text Classification Using Hugging Face Transformers
Text Summarization is a process of generating a compact and meaningful synopsis from a huge volume of text. Sources for such text include news articles, blogs, social media posts, all kinds of documentation, and many more. If you are new to NLP and want to read more about text summarization, this article will help you understand the basic and advanced concepts. The … [Read more...] about Extractive Text Summarization Using Contextual Embeddings
This notebook is designed to use a pretrained transformers model and fine-tune it on a classification task. The focus of this tutorial will be on the code itself and how to adjust it to your needs.This notebook is using the AutoClasses from transformer by Hugging Face functionality. This functionality can guess a model’s configuration, tokenizer and … [Read more...] about Fine-tune Transformers in PyTorch Using Hugging Face Transformers