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An Introduction to BigBird

Analytics Vidhya

Source: Canva|Arxiv Introduction In 2018 GoogleAI researchers developed Bidirectional Encoder Representations from Transformers (BERT) for various NLP tasks. This article was published as a part of the Data Science Blogathon.

BERT 390
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Introduction to DistilBERT in Student Model

Analytics Vidhya

Source: Canva Introduction In 2018, GoogleAI researchers released the BERT model. It was a fantastic work that brought a revolution in the NLP domain. This article was published as a part of the Data Science Blogathon. However, the BERT model did have some drawbacks i.e. it was bulky and hence a little slow. To navigate […].

BERT 373
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Text Classification using BERT and TensorFlow

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction In 2018, a powerful Transformer-based machine learning model, namely, BERT was developed by Jacob Devlin and his colleagues from Google for NLP applications.

BERT 373
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ALBERT Model for Self-Supervised Learning

Analytics Vidhya

Source: Canva Introduction In 2018, Google AI researchers came up with BERT, which revolutionized the NLP domain. This article was published as a part of the Data Science Blogathon.

BERT 338
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Automated Fine-Tuning of LLAMA2 Models on Gradient AI Cloud

Analytics Vidhya

However, in 2018, the “Universal Language Model Fine-tuning for Text Classification” paper changed the entire landscape of Natural Language Processing (NLP). Introduction Welcome to the world of Large Language Models (LLM). In the old days, transfer learning was a concept mostly used in deep learning.

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NLP Rise with Transformer Models | A Comprehensive Analysis of T5, BERT, and GPT

Unite.AI

Natural Language Processing (NLP) has experienced some of the most impactful breakthroughs in recent years, primarily due to the the transformer architecture. The introduction of word embeddings, most notably Word2Vec, was a pivotal moment in NLP. One-hot encoding is a prime example of this limitation.

BERT 298
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Systematic Reviews in NLP

Ehud Reiter

Over the past year I have on several occasions encouraged NLP researchers to do systematic reviews of the research literature. I In AI and NLP, most literature surveys are like “previous work” sections in papers. The I describe the concept below, I think it is a very useful tool in many contexts!

NLP 146