tashengjinsheng Goto Github PK

albert_tiny_zh

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

annotated-transformer

http://nlp.seas.harvard.edu/2018/04/03/attention.html

app

test

awesome-instruction-dataset

A collection of open-source dataset to train instruction-following LLMs (ChatGPT,LLaMA,Alpaca)

bert

TensorFlow code and pre-trained models for BERT

bert-pytorch

Google AI 2018 BERT pytorch implementation

bert_score

BERT score for text generation

characters

中文停用词/常用汉字/生僻字集合

chinese-bert-wwm

Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）

chinese-nlp-corpus

Collections of Chinese NLP corpus

chinese-poetry

The most comprehensive database of Chinese poetry 🧶最全中华古诗词数据库, 唐宋两朝近一万四千古诗人, 接近5.5万首唐诗加26万宋诗. 两宋时期1564位词人，21050首词。

chinese-text-classification-pytorch

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

chinese_medical_nlp

中文医疗NLP领域 数据集，论文 ，知识图谱，语料，工具包

chineseblue

Chinese Biomedical Language Understanding Evaluation benchmark (ChineseBLUE)

clue

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

cluedatasetsearch

搜索所有中文NLP数据集，附常用英文NLP数据集

cnn-dailymail

Code to obtain the CNN / Daily Mail dataset (non-anonymized) for summarization

covid-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

covid-dialogue

crawler

assemble multi crawl tools

dane

datasets

Poetry-related datasets developed by THUAIPoet (Jiuge) group.

deep-learning-interview-book

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

depix

Recovers passwords from pixelized screenshots

dialog_corpus

用于训练中英文对话系统的语料库 Datasets for Training Chatbot System

dreamtime

Use artificial intelligence to create fake nudes.

epidemicassistant

ernie

An Implementation of ERNIE For Language Understanding (including Pre-training models and Fine-tuning tools)

external-attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐