sentence2vecDeep sentence embedding using Sequence to Sequence learning
Stars: ✭ 23 (-41.03%)
Mutual labels: seq2seq
YodaSpeakTranslating English to Yoda English using Sequence-to-Sequence with Tensorflow.
Stars: ✭ 25 (-35.9%)
Mutual labels: seq2seq
fiction generatorFiction generator with Tensorflow. 模仿王小波的风格的小说生成器
Stars: ✭ 27 (-30.77%)
Mutual labels: seq2seq
keras-chatbot-web-apiSimple keras chat bot using seq2seq model with Flask serving web
Stars: ✭ 51 (+30.77%)
Mutual labels: seq2seq
deep-keyphraseseq2seq based keyphrase generation model sets, including copyrnn copycnn and copytransfomer
Stars: ✭ 51 (+30.77%)
Mutual labels: seq2seq
CVAE DialCVAE_XGate model in paper "Xu, Dusek, Konstas, Rieser. Better Conversations by Modeling, Filtering, and Optimizing for Coherence and Diversity"
Stars: ✭ 16 (-58.97%)
Mutual labels: seq2seq
lstm-mathNeural network that solves math equations on the character level
Stars: ✭ 26 (-33.33%)
Mutual labels: seq2seq
Shakespearizing-Modern-EnglishCode for "Jhamtani H.*, Gangal V.*, Hovy E. and Nyberg E. Shakespearizing Modern Language Using Copy-Enriched Sequence to Sequence Models" Workshop on Stylistic Variation, EMNLP 2017
Stars: ✭ 64 (+64.1%)
Mutual labels: seq2seq
FontRNNImplementation of FontRNN [Computer Graphics Forum, 2019].
Stars: ✭ 27 (-30.77%)
Mutual labels: seq2seq
transformerA PyTorch Implementation of "Attention Is All You Need"
Stars: ✭ 28 (-28.21%)
Mutual labels: seq2seq
adversarial-code-generationSource code for the ICLR 2021 work "Generating Adversarial Computer Programs using Optimized Obfuscations"
Stars: ✭ 16 (-58.97%)
Mutual labels: seq2seq
minimal-nmtA minimal nmt example to serve as an seq2seq+attention reference.
Stars: ✭ 36 (-7.69%)
Mutual labels: seq2seq
BERT-NERUsing pre-trained BERT models for Chinese and English NER with 🤗Transformers
Stars: ✭ 114 (+192.31%)
Mutual labels: seq2seq
DeepLearning-LabCode lab for deep learning. Including rnn,seq2seq,word2vec,cross entropy,bidirectional rnn,convolution operation,pooling operation,InceptionV3,transfer learning.
Stars: ✭ 83 (+112.82%)
Mutual labels: seq2seq
RNNSearchAn implementation of attention-based neural machine translation using Pytorch
Stars: ✭ 43 (+10.26%)
Mutual labels: seq2seq
NeuralCitationNetworkNeural Citation Network for Context-Aware Citation Recommendation (SIGIR 2017)
Stars: ✭ 24 (-38.46%)
Mutual labels: seq2seq
Nuts自然语言处理常见任务(主要包括文本分类,序列标注,自动问答等)解决方案试验田
Stars: ✭ 21 (-46.15%)
Mutual labels: seq2seq