Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Tengine | 4,452 | 6 months ago | 244 | apache-2.0 | C++ | |||||
Tengine is a lite, high performance, modular inference engine for embedded device | ||||||||||
Nlp_tutorial | 1,309 | 2 years ago | 2 | |||||||
NLP超强入门指南,包括各任务sota模型汇总(文本分类、文本匹配、序列标注、文本生成、语言模型),以及代码、技巧 | ||||||||||
Neusum | 118 | 6 years ago | 3 | Python | ||||||
Code for the ACL 2018 paper "Neural Document Summarization by Jointly Learning to Score and Select Sentences" | ||||||||||
R Men | 70 | 2 years ago | 1 | apache-2.0 | Python | |||||
Transformer-based Memory Networks for Knowledge Graph Embeddings (ACL 2020) (Pytorch and Tensorflow) | ||||||||||
Torch Teacher | 45 | 8 years ago | Lua | |||||||
Compilation of the state-of-the-art neural models used in Machine Reading and Comprehension Task (in progress) | ||||||||||
Mrnet | 44 | 5 years ago | 1 | mit | Python | |||||
Implementation of the paper: Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet | ||||||||||
Tensorflow Hrt | 32 | 6 years ago | 9 | apache-2.0 | C++ | |||||
Heterogeneous Run Time version of TensorFlow. Added heterogeneous capabilities to the TensorFlow, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original TensorFlow architecture which users deploy their applications seamlessly. | ||||||||||
Mrnet | 17 | 5 years ago | 2 | mit | Python | |||||
PyTorch implementation of the MRNet paper, developed for the MRNet Competition hosted by the Stanford ML Group | ||||||||||
Bilingual Word Embeddings With Bucketed Cnn For Parallel Sentence Extraction | 11 | 6 years ago | 1 | mit | Python | |||||
Code for our paper in ACL 2017 | ||||||||||
Hlt Hitsz.github.io | 9 | 4 years ago | ||||||||
Weekly Paper Reading Group of HLT-HITSZ |