A neural chatbot using sequence to sequence model with attentional decoder. This is a fully functional chatbot. This is based on Google Translate Tensorflow modelhttps://github.com/tensorflow/models/blob/master/tutorials/rnn/translate/ Sequence to sequence model by Cho et al.(2014) Created by Chi...
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation. (Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi, Luke Zettlemoyer. ACL 2017) Requirements The pre-trained models only run on GPUs, so you will need to have the following installed: Latest NVIDIA driver CUDA 8 To...
零、背景及引言 本文是对Sequence to Sequence Learning with Neural Networks文章阅读后的总结。 在不同的学习任务中,传统深度神经网络(DNN)是表现不错的强力模型,如在图像分类、语音识别领域,但DNN由于不能适应输入输出不固定的情况,导致其不能够用于序列到序列的映射任务。 在2014年,Google的三位作者提出基于端到...
Order matters: sequence to sequence for sets. In: Bengio, Y. & LeCun, Y. (eds.) Proc. 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2–4, 2016, Conference Track Proceedings (2016). Yang, K. et al. Analyzing learned molecular ...
GPT2:CarryMeRookie:大模型系列论文 GPT2: Language Models are Unsupervised Multitask Learners Sequence to Sequence Learning with Neural Networks 摘要 深度神经网络(DNNs)是强大的模型,已在困难的学习任务上取得了出色的表现。尽管当有大量标记的训练集可用时,DNNs表现良好,但它们不能用于将序列映射到序列。在本文...
1.1 为什么选择序列模型?(Why Sequence Models?) 在本课程中你将学会序列模型,它是深度学习中最令人激动的内容之一。循环神经网络(RNN)之类的模型在语音识别、自然语言处理和其他领域中引起变革。在本节课中,你将学会如何自行创建这些模型。我们先看一些例子,这些例子都有效使用了序列模型。
Abstractive Text Summarization with Sequence-to-Sequence Models Tian Shi,Yaser Keneshloo,Naren Ramakrishnan,Chandan K. Reddy Requirements and Installation Python 3.5.2 glob argparse shutil pytorch 1.0 Use following scripts to Set up GPU, cuda and pytorch ...
Variational Attention for Sequence-to-Sequence Models. ICML, 2018. Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs.ACL, 2020. On the Importance of Diversity in Question Generation for QA.ACL, 2020. ...
Higher-level components for building new models, including generic neural network structures like sequence-to-sequence models and components for modeling and transforming probability distributions Data loading and iterators for time series data, including a mechanism for transforming the data before it is...
You will build a Neural Machine Translation (NMT) model to translate human readable dates ("25th of June, 2009") into machine readable dates ("2009-06-25"). You will do this using an attention model, one of the most sophisticated sequence to sequence models. ...