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The InfoGAN repository contains the original implementation used to reproduce the results in the paper “InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets”. InfoGAN is a variant of the GAN (Generative Adversarial Network) architecture that aims to learn disentangled and interpretable latent representations by maximizing the mutual information between a subset of the latent codes and the generated outputs.
Flexible text-to-text transformer model for multilingual NLP tasks
...Its flexible architecture and consistent input/output format simplify model reuse and transfer learning across different NLP tasks. T5-base achieves competitive performance across 24 language understanding tasks, as documented in its research paper.