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Modern NLP: A Detailed Overview. Part 3: BERT

Towards AI

In this article, we will talk about another and one of the most impactful works published by Google, BERT (Bi-directional Encoder Representation from Transformers) BERT undoubtedly brought some major improvements in the NLP domain. Then, Finally, we come to BERT.

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Introduction to Large Language Models (LLMs): An Overview of BERT, GPT, and Other Popular Models

John Snow Labs

In this section, we will provide an overview of two widely recognized LLMs, BERT and GPT, and introduce other notable models like T5, Pythia, Dolly, Bloom, Falcon, StarCoder, Orca, LLAMA, and Vicuna. BERT excels in understanding context and generating contextually relevant representations for a given text.

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UC Berkeley Researchers Propose CRATE: A Novel White-Box Transformer for Efficient Data Compression and Sparsification in Deep Learning

Marktechpost

Such a representation makes many subsequent tasks, including those involving vision, classification, recognition and segmentation, and generation, easier. Therefore, encoders, decoders, and auto-encoders can all be implemented using a roughly identical crate design.

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Amazon EC2 DL2q instance for cost-efficient, high-performance AI inference is now generally available

AWS Machine Learning Blog

Model category Number of models Examples​ NLP​ 157 BERT, BART, FasterTransformer, T5, Z-code MOE Generative AI – NLP 40 LLaMA, CodeGen, GPT, OPT, BLOOM, Jais, Luminous, StarCoder, XGen Generative AI – Image 3 Stable diffusion v1.5 opt/qti-aic/exec/qaic-exec -m=bert-base-cased/generatedModels/bert-base-cased_fix_outofrange_fp16.onnx

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3 LLM Architectures

Mlearning.ai

1️⃣ Autoencoders  — In auto-encoders, the decoder part of the transformer is discarded after pre-training and only the encoder is used to generated the output. The widely popular BERT and RoBERTa models were based on this architecture and performed well on sentiment analysis and text classification .

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Accelerate hyperparameter grid search for sentiment analysis with BERT models using Weights & Biases, Amazon EKS, and TorchElastic

AWS Machine Learning Blog

Transformer-based language models such as BERT ( Bidirectional Transformers for Language Understanding ) have the ability to capture words or sentences within a bigger context of data, and allow for the classification of the news sentiment given the current state of the world. The code can be found on the GitHub repo. eks-create.sh

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What are the Different Types of Transformers in AI

Mlearning.ai

In this article, we will delve into the three broad categories of transformer models based on their training methodologies: GPT-like (auto-regressive), BERT-like (auto-encoding), and BART/T5-like (sequence-to-sequence). Auto Regression is common in more than just Transformers.