Snli_nn
hacking on the stanford natural language inference (SNLI) corpus (in theano)
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Nlu | 775 | 4 months ago | 35 | apache-2.0 | Python | |||||
| 1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems. | ||||||||||
| Nlp_pytorch_project | 517 | a year ago | 15 | Python | ||||||
| Embedding, NMT, Text_Classification, Text_Generation, NER etc. | ||||||||||
| Deepnlp Course | 479 | 5 years ago | 4 | Jupyter Notebook | ||||||
| Deep NLP Course | ||||||||||
| Machine Learning | 25 | 7 years ago | 3 | Jupyter Notebook | ||||||
| notes and exercises | ||||||||||
| Sentence2vec | 24 | 7 years ago | mit | Jupyter Notebook | ||||||
| Deep sentence embedding using Sequence to Sequence learning | ||||||||||
| Hierarchical Seq2seq | 22 | 6 years ago | 3 | Python | ||||||
| A PyTorch implementation of the hierarchical encoder-decoder architecture (HRED) introduced in Sordoni et al (2015). It is a hierarchical encoder-decoder architecture for modeling conversation triples in the MovieTriples dataset. This version of the model is built for the MovieTriples dataset. | ||||||||||
| Embedding | 19 | 3 years ago | 1 | Python | ||||||
| Embedding模型代码和学习笔记总结 | ||||||||||
| Snli_nn | 13 | 8 years ago | mit | Python | ||||||
| hacking on the stanford natural language inference (SNLI) corpus (in theano) | ||||||||||
| Natural Language Processing Tutorials | 12 | 2 years ago | mit | Jupyter Notebook | ||||||
| NLP Webinars Created for Udacity's Mentorship Program (2019). | ||||||||||
| Joint Semantic Phonetic Embedding | 10 | 3 years ago | n,ull | mit | Jupyter Notebook | |||||
| We use phonetics as a feature to create a joint semantic-phonetic embedding and improve the neural machine translation between Chinese and Japanese. 🥳 | ||||||||||
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