Multi Task Vision and Language

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

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

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

RoBERTa中文预训练模型: RoBERTa for Chinese

Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

The ChID Dataset for paper ChID: A Large-scale Chinese IDiom Dataset for Cloze Test

Recognition to Cognition Networks (code for the model in "From Recognition to Cognition: Visual Commonsense Reasoning", CVPR 2019)

TensorFlow code and pre-trained models for BERT

Conceptual Captions is a dataset containing (image-URL, caption) pairs designed for the training and evaluation of machine learned image captioning systems.

100+ Chinese Word Vectors 上百种预训练中文词向量

Deep Learning and applications in Startups, CV, Text Mining, NLP

Baseline Systems of DuReader Dataset

Code for the ACL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks"

Tensorflow Faster RCNN for Object Detection

The PyTorch Implementation of SummaRuNNer