| artetxem/undreamt |
421 |
|
0 |
0 |
almost 6 years ago |
0 |
|
11 |
gpl-3.0 |
Python |
| Unsupervised Neural Machine Translation |
| artetxem/monoses |
183 |
|
0 |
0 |
over 5 years ago |
0 |
|
5 |
gpl-3.0 |
Java |
| Unsupervised Statistical Machine Translation |
| lium-lst/nmtpy |
128 |
|
0 |
0 |
about 8 years ago |
0 |
|
0 |
other |
Python |
| nmtpy is a Python framework based on dl4mt-tutorial to experiment with Neural Machine Translation pipelines. |
| jwieting/para-nmt-50m |
99 |
|
0 |
0 |
over 2 years ago |
0 |
|
1 |
bsd-3-clause |
Python |
| Pre-trained models and code and data to train and use models from "Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations" |
| ZhenYangIACAS/unsupervised-NMT |
90 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
|
Python |
| Unsupervised neural machine translation; weight sharing; GAN |
| neulab/word-embeddings-for-nmt |
66 |
|
0 |
0 |
almost 6 years ago |
0 |
|
1 |
|
Python |
| Supplementary material for "When and Why Are Pre-trained Word Embeddings Useful for Neural Machine Translation?" at NAACL 2018 |
| dipanjanS/nlp_workshop_odsc_europe20 |
36 |
|
0 |
0 |
over 5 years ago |
0 |
|
0 |
gpl-3.0 |
Jupyter Notebook |
| Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and Topic Models. |
| Imagist-Shuo/UNMT-SPR |
29 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
mit |
Python |
| Implementation of “Unsupervised Neural Machine Translation with SMT as Posterior Regularization” (AAAI 2019) |
| UriSha/EmbeddinglessNMT |
28 |
|
0 |
0 |
almost 5 years ago |
0 |
|
0 |
mit |
Python |
| The implementation of "Neural Machine Translation without Embeddings" |
| xiadingZ/video-caption-openNMT.pytorch |
26 |
|
0 |
0 |
almost 8 years ago |
0 |
|
1 |
mit |
Python |
| implement video caption based on openNMT |
