Large Language Model (LLM/NLP) : RoBERTA vs. BERT vs. XLNet for Word Prediction

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This video discusses predicting MASKed words using pre-trained models: RoBERTa, BERT, and XLNet. The dataset used for pre-training is wiki103. The platform used is Google Colab, which allows users to access limited free versions of GPU and TPU.

About the Author:
Dr. Ray Islam is a strategist and an expert in Generative AI. He also teaches Natural Language Processing (GenAI)) at George Mason University, Fairfax, VA. and Cyber Security at the University of Maryland, College Park. Dr. Ray holds 5 degrees from 5 different countries spanning 3 different continents. With a distinguished career, he has held leadership roles in AI and ML at notable firms like Deloitte, Raytheon, Lockheed Martin and others. He has consulted for The National Aeronautics and Space Administration (NASA), The General Services Administration (GSA), Berkshire Hathaway, and American Institutes for Research (AIR) among others. In his leadership role at Deloitte, he spearheaded strategies for the Generative AI and Model Foundry team. Dr. Ray boasts a PhD from the University of Maryland, College Park, and holds degrees from Canada, Scotland, England. He is an associate editor of Journal of Prognostics and Health Management (IJPHM), published by Carleton University, Canada, and a reviewer for the journal of Reliability Engineering and System Safety, published by Elsevier. His primary research areas are AIML, Generative AI (NLP/LLM and Computer Vision), XAI, and AI ethics.

  1. Ray ISL
  2. BERT
  3. RoBERTa
  4. XLNet
  5. Word Prediction
  6. Google Colab
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