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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/h2oai/h2ogpt

h2oGPT: Democratizing Large Language Models

https://github.com/h4ste/oscar

Attention Is All You Need

https://github.com/hahahappyboy/GANForCartoon

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/haidershaour/bert

Attention Is All You Need

https://github.com/hakeematyab/Neural-Image-Caption-Generator-Show-and-Tell-Paper-Replication

Show and Tell: A Neural Image Caption Generator

https://github.com/hakillha/yolact_yx

YOLACT: Real-time Instance Segmentation

https://github.com/halo090770/bert

Attention Is All You Need

https://github.com/hampen2929/yolact

YOLACT: Real-time Instance Segmentation

https://github.com/han-shi/SparseBERT

Attention Is All You Need

https://github.com/hannibal046/nanorwkv

Attention Is All You Need

https://github.com/hanq0212/IIAE-Pytorch

Variational Interaction Information Maximization for Cross-domain Disentanglement

https://github.com/hansam95/nmg

Zero-shot Image-to-Image Translation

https://github.com/hansongfang/CompNet

Compositionally Generalizable 3D Structure Prediction

https://github.com/hao-ai-lab/Consistency_LLM

Accelerating Transformer Inference for Translation via Parallel Decoding

https://github.com/hao-ai-lab/lookaheaddecoding

Accelerating Transformer Inference for Translation via Parallel Decoding

https://github.com/happy-jihye/Cartoon-StyleGAN

Fine-Tuning StyleGAN2 For Cartoon Face Generation

https://github.com/haratzouvara/image_restoration

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/harenlin/IMDB-Sentiment-Analysis-Using-BERT-Fine-Tuning

Attention Is All You Need

https://github.com/hariv/pix2pix

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/harshit158/paper-dots

Attention Is All You Need

https://github.com/harshitbhushan68/Pix-2-Pix

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/harshithbelagur/Neural-Machine-Translation

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/harvardnlp/annotated-transformer

Attention Is All You Need

https://github.com/hashi0203/image-captioning

Show and Tell: A Neural Image Caption Generator

https://github.com/hazdzz/AdaNorm

Understanding and Improving Layer Normalization

https://github.com/hcholab/k-salsa

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

https://github.com/he1ght/BiBERT_CE

BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation

https://github.com/heljakka/img-transformer-chain

Recursive Chaining of Reversible Image-to-image Translators For Face Aging

https://github.com/hello-world-cc/starGANv1-Pytorch

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

https://github.com/hero9968/pix2pix-tensorflow

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/hfxunlp/transformer

Attention Is All You Need

https://github.com/hhy37/tensor2tensor

Tensor2Tensor for Neural Machine Translation

https://github.com/hihellohowareyou/RESREF_Chatbot_data_for_Korean

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

https://github.com/hikaruya8/lstm_model_py

Recurrent Neural Network Regularization

https://github.com/histocartography/histocartography

HistoCartography: A Toolkit for Graph Analytics in Digital Pathology

https://github.com/hiun/learning-transformers

Neural Machine Translation by Jointly Learning to Align and Translate

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