https://github.com/KoshiroSato/Flask_NLP_App
mT5: A massively multilingual pre-trained text-to-text transformer
Papers with Code 아카이브
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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/KoshiroSato/Simple_Transformers_mT5_finetuning
mT5: A massively multilingual pre-trained text-to-text transformer
https://github.com/Kprerak-iisc/data-science
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/KrishnaTarun/Deep-Learning-Lab
https://github.com/KrishnaswamyLab/travelgan
TraVeLGAN: Image-to-image Translation by Transformation Vector Learning
https://github.com/KuldeepSangwan/MachineTranslation
Neural Machine Translation for Low-Resourced Indian Languages
https://github.com/KushGrandhi/Polaroid
https://github.com/KwonGihyun/DiagonalGAN
https://github.com/Kyubyong/transformer
https://github.com/Kyubyong/word2word
word2word: A Collection of Bilingual Lexicons for 3,564 Language Pairs
https://github.com/LKLQQ/StarGAN
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
https://github.com/Lamikins/public_exp
An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution
https://github.com/LaurentVe/Automatic-image-Captioning
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
https://github.com/LawrenceDuan/myLASER
Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings
https://github.com/LeBenchmark/Interspeech2021
https://github.com/Legend94rz/spatial-transformer
https://github.com/Leinadh/avatar-image-generator
XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings
https://github.com/Lemoners/Attention-Is-All-You-Need
https://github.com/LeoWood/bert-horovod
https://github.com/LeslieZhoa/DCT-NET.Pytorch
DCT-Net: Domain-Calibrated Translation for Portrait Stylization
https://github.com/LiYuhangUSTC/Sketch2Face
https://github.com/LiamMaclean216/Pytorch-Chatbot
https://github.com/LiamMaclean216/Pytorch-Transfomer
https://github.com/Liangtaiwan/lang-rep
Looking for Clues of Language in Multilingual BERT to Improve Cross-lingual Generalization
https://github.com/LinXueyuanStdio/LaTeX_OCR
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
https://github.com/LinXueyuanStdio/LaTeX_OCR_PRO
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
https://github.com/Liut2016/stackedResBiLSTM
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/LiyuanLucasLiu/Transforemr-Clinic
https://github.com/LiyuanLucasLiu/Transformer-Clinic
https://github.com/Lornatang/PyTorch-CycleGAN
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/Lotayou/CoCosNet
Cross-domain Correspondence Learning for Exemplar-based Image Translation
https://github.com/LouisRouss/Diffusion-Based-Model-for-Colorization
https://github.com/LoveYang/bert_test
https://github.com/Lsdefine/attention-is-all-you-need-keras
https://github.com/Luccadoremi/Model-Compression-DAQ
HAT: Hardware-Aware Transformers for Efficient Natural Language Processing
https://github.com/Lukasz-G/Hydra
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.