Kakao Brain Corp.
Location:Pankyo, Seongnam, Kyungki, Republic of Korea
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Official Implementation of 'Fast AutoAugment' in PyTorch.
PORORO: Platform Of neuRal mOdels for natuRal language prOcessing
KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)
A GPipe implementation in PyTorch
PyTorch implementation of a 1.3B text-to-image generation model trained on 14 million image-text pairs
The official implementation of Autoregressive Image Generation using Residual Quantization (CVPR '22)
Easy-to-use word-to-word translations for 3,564 language pairs.
A LARS implementation in PyTorch
A Neural Grapheme-to-Phoneme Conversion Package for Mandarin Chinese Based on a New Open Benchmark Dataset
KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding
A specially designed light version of Fast AutoAugment
Official repository for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'21, Oral Presentation)
PyTorch Implementation of Spatially Consistent Representation Learning(SCRL)
The code and models for "An Empirical Study of Tokenization Strategies for Various Korean NLP Tasks" (AACL-IJCNLP 2020)
PyTorch Implementation of Sparse DETR
Team Kakao&Brain's Grammatical Error Correction System for the ACL 2019 BEA Shared Task
Jejueo Datasets for Machine Translation and Speech Synthesis
Official repository for Automated Learning Rate Scheduler for Large-Batch Training (8th ICML Workshop on AutoML)
An Empirical Study of Invariant Risk Minimization
Official PyTorch implementation of MIRO
"Learning Loss for Test-Time Augmentation (NeurIPS 2020)"
brain cloud hyperopt example (mnist)