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https://github.com/dsksd/deepnlp-models-pytorch
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
https://github.com/dsksd/deepnlp-models-pytorch
cs-224n deep-learning deep-nlp-models natural-language-processing neural-network nlp pytorch rnn stanford-univ
Last synced: 4 days ago
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Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
- Host: GitHub
- URL: https://github.com/dsksd/deepnlp-models-pytorch
- Owner: DSKSD
- License: mit
- Created: 2017-08-16T01:22:16.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2019-10-15T03:26:36.000Z (over 5 years ago)
- Last Synced: 2025-01-18T02:01:56.182Z (4 days ago)
- Topics: cs-224n, deep-learning, deep-nlp-models, natural-language-processing, neural-network, nlp, pytorch, rnn, stanford-univ
- Language: Jupyter Notebook
- Size: 1.25 MB
- Stars: 2,956
- Watchers: 111
- Forks: 660
- Open Issues: 11
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# DeepNLP-models-Pytorch
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ: NLP with Deep Learning)
- This is not for Pytorch beginners. If it is your first time to use Pytorch, I recommend these [awesome tutorials](#references).
- If you're interested in DeepNLP, I strongly recommend you to work with this awesome lecture.
* cs-224n-slides
* cs-224n-videos
This material is not perfect but will help your study and research:) Please feel free to pull requests!!
## Contents
| Model | Links |
| ------------- |:-------------:|
| 01. Skip-gram-Naive-Softmax | [notebook / data / paper] |
| 02. Skip-gram-Negative-Sampling | [notebook / data / paper] |
| 03. GloVe | [notebook / data / paper] |
| 04. Window-Classifier-for-NER | [notebook / data / paper] |
| 05. Neural-Dependancy-Parser | [notebook / data / paper] |
| 06. RNN-Language-Model | [notebook / data / paper] |
| 07. Neural-Machine-Translation-with-Attention | [notebook / data / paper] |
| 08. CNN-for-Text-Classification | [notebook / data / paper] |
| 09. Recursive-NN-for-Sentiment-Classification | [notebook / data / paper] |
| 10. Dynamic-Memory-Network-for-Question-Answering | [notebook / data / paper] |
## Requirements
- Python 3.5
- Pytorch 0.2+
- nltk 3.2.2
- gensim 2.2.0
- sklearn_crfsuite
## Getting started
`git clone https://github.com/DSKSD/cs-224n-Pytorch.git`
### prepare dataset
````
cd script
chmod u+x prepare_dataset.sh
./prepare_dataset.sh
````
### docker env
ubuntu 16.04 python 3.5.2 with various of ML/DL packages including tensorflow, sklearn, pytorch
`docker pull dsksd/deepstudy:0.2`
````
pip3 install docker-compose
cd script
docker-compose up -d
````
### cloud setting
`not yet`
## References
* practical-pytorch
* DeepLearningForNLPInPytorch
* pytorch-tutorial
* pytorch-examples
## Author
Sungdong Kim / @DSKSD