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Implementation for paper: Improving Neural Machine Translation with the Abstract Meaning Representation by Combining Graph and Sequence Transformers
A plugin for Mac WeChat
Efficient and minimal collaborative code editor, self-hosted, no database required
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.
Neural Abstractive Text Summarization with Sequence-to-Sequence Models
XTREME is a benchmark for the evaluation of the cross-lingual generalization ability of pre-trained multilingual models that covers 40 typologically diverse languages and includes nine tasks.
Ranking of Top Institutes for Natural Language Processing (NLP)
Modular implementation of an AM dependency parser in AllenNLP.
AMR-to-text Generation with Graph Transformer
Heterogeneous Graph Transformer for Graph-to-Sequence Learning
Code for the paper "Adaptive Transformers for Learning Multimodal Representations" (ACL SRW 2020)
ACL 2020 Unsupervised Opinion Summarization as Copycat-Review Generation
[ACL'20, IJCAI'20] Code for "Efficient Second-Order TreeCRF for Neural Dependency Parsing" and "Fast and Accurate Neural CRF Constituency Parsing".
This repository contains the code for "BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Representations".
一个在你编程时疯狂称赞你的 VSCode 扩展插件 | An VSCode extension that keeps giving you compliment while you are coding, it will checks the keywords of code to play suitable sounds.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.
A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.
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