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Understanding BERT

Mlearning.ai

Pre-training of Deep Bidirectional Transformers for Language Understanding BERT is a language model that can be fine-tuned for various NLP tasks and at the time of publication achieved several state-of-the-art results. Finally, the impact of the paper and applications of BERT are evaluated from today’s perspective. 1 Architecture III.2

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Google Research, 2022 & beyond: Algorithmic advances

Google Research AI blog

In 2022, we continued this journey, and advanced the state-of-the-art in several related areas. We also had a number of interesting results on graph neural networks (GNN) in 2022. Top Market algorithms and causal inference We also continued our research in improving online marketplaces in 2022.

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Google Research, 2022 & beyond: Algorithms for efficient deep learning

Google Research AI blog

In 2022, we focused on new techniques for infusing external knowledge by augmenting models via retrieved context; mixture of experts; and making transformers (which lie at the heart of most large ML models) more efficient. Google Research, 2022 & beyond This was the fourth blog post in the “Google Research, 2022 & Beyond” series.

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Google at EMNLP 2022

Google Research AI blog

Posted by Malaya Jules, Program Manager, Google This week, the premier conference on Empirical Methods in Natural Language Processing (EMNLP 2022) is being held in Abu Dhabi, United Arab Emirates. We are proud to be a Diamond Sponsor of EMNLP 2022, with Google researchers contributing at all levels.

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Google Research, 2022 & Beyond Series

Bugra Akyildiz

We are heavy Google Research posts this week, enjoy specifically the 2022 & Beyond series! Bert paper has demos from HF spaces and Replicate. Libraries MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.

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Google Research, 2022 & beyond: Research community engagement

Google Research AI blog

In 2022, we expanded our research interactions and programs to faculty and students across Latin America , which included grants to women in computer science in Ecuador. See some of the datasets and tools we released in 2022 listed below. We work towards inclusive goals and work across the globe to achieve them.

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Unlock the Power of BERT-based Models for Advanced Text Classification in Python

John Snow Labs

Text classification with transformers involves using a pretrained transformer model, such as BERT, RoBERTa, or DistilBERT, to classify input text into one or more predefined categories or labels. BERT (Bidirectional Encoder Representations from Transformers) is a language model that was introduced by Google in 2018.

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