Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language generation.

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...

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Too Long; Didn't Read This tutorial walks you through fine-tuning a ResNet-18 model from TensorFlow’s Model Garden for classifying images in the CIFAR-10 dataset. You’ll learn how to set up the ...

Abstract: The present paper investigates the application of TensorFlow Lite to deploy the Convolutional Neural Network on Rasberry Pi for real-time image classification, considering specifically the ...

Abstract: Text classification is a critical task for understanding the knowledge behind text, especially in medical text. In this paper, we propose a medical graph diffusion model, named the MGD model ...

It is a universal phenomenon for patients who do not know which clinical department to register in large general hospitals. Although triage nurses can help patients, due to the larger number of ...

Cyrillic Mongolian text classification with tensorflow 2, and also some fine-tuning on TugsTugi's Mongolian BERT model and other NLP experiments are included.