yzhangcs

perturbed_masking

基于BERT的无监督分词和句法分析

latex-to-html5

Scripts for Latex to HTML5 conversion

tikzplotlib

:bar_chart: Save matplotlib figures as TikZ/PGFplots for smooth integration into LaTeX.

tqdm

:zap: A Fast, Extensible Progress Bar for Python and CLI

urnng

gtos

Code for AAAI2020 paper "Graph Transformer for Graph-to-Sequence Learning"

GitHub520

:kissing_heart: 让你“爱”上 GitHub，解决访问时图裂、加载慢的问题。（无需安装）

gpt-3

GPT-3: Language Models are Few-Shot Learners

InOrderSeq2seq

maxspn

Algorithms in the paper "Maximum A Posteriori Inference in Sum-Product Networks"

vqa-sva

Structured Attentions for Visual Question Answering

CRFAE-Dep-Parser

whiteglass

Minimal, responsive Jekyll theme for hackers

berkeleyparser

Automatically exported from code.google.com/p/berkeleyparser

Flat-Lattice-Transformer

code for ACL 2020 paper: FLAT: Chinese NER Using Flat-Lattice Transformer

pytorch-rnng

CLUE

中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard

MTBook

《机器翻译：基础与模型》肖桐 朱靖波 著 - Machine Translation: Foundations and Models

PyTorch-PtrNet

PyTorch implementation of PtrNet to solve sorting problem.

clip-as-service

🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

text2sql-data

A collection of datasets that pair questions with SQL queries.

pytorch-lightning

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

lixin4ever.github.io

comparxiv

Compare two version of an arXiv preprint with a single command.

nndl.github.io

《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

spider-schema-gnn-global

Author implementation of Global Reasoning over Database Structures for Text-to-SQL Parsing

dep2label-up

Dependency Parsing as Sequence Labeling with Python3+ and PyTorch1+ and MTL

pyGAT

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

Transformer-Clinic

Understanding the Difficulty of Training Transformers