{"id":15033106,"url":"https://github.com/dsksd/deepnlp-models-pytorch","last_synced_at":"2025-05-15T10:02:39.896Z","repository":{"id":45376837,"uuid":"100433896","full_name":"DSKSD/DeepNLP-models-Pytorch","owner":"DSKSD","description":"Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)","archived":false,"fork":false,"pushed_at":"2019-10-15T03:26:36.000Z","size":1309,"stargazers_count":2954,"open_issues_count":11,"forks_count":656,"subscribers_count":110,"default_branch":"master","last_synced_at":"2025-05-15T10:02:30.555Z","etag":null,"topics":["cs-224n","deep-learning","deep-nlp-models","natural-language-processing","neural-network","nlp","pytorch","rnn","stanford-univ"],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DSKSD.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-08-16T01:22:16.000Z","updated_at":"2025-05-11T00:51:20.000Z","dependencies_parsed_at":"2022-07-13T21:44:20.465Z","dependency_job_id":null,"html_url":"https://github.com/DSKSD/DeepNLP-models-Pytorch","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DSKSD%2FDeepNLP-models-Pytorch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DSKSD%2FDeepNLP-models-Pytorch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DSKSD%2FDeepNLP-models-Pytorch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DSKSD%2FDeepNLP-models-Pytorch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DSKSD","download_url":"https://codeload.github.com/DSKSD/DeepNLP-models-Pytorch/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254319716,"owners_count":22051072,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cs-224n","deep-learning","deep-nlp-models","natural-language-processing","neural-network","nlp","pytorch","rnn","stanford-univ"],"created_at":"2024-09-24T20:20:07.164Z","updated_at":"2025-05-15T10:02:32.977Z","avatar_url":"https://github.com/DSKSD.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DeepNLP-models-Pytorch\n\nPytorch implementations of various Deep NLP models in \u003ca href=\"http://web.stanford.edu/class/cs224n/\"\u003ecs-224n(Stanford Univ: NLP with Deep Learning)\u003c/a\u003e\n\n- This is not for Pytorch beginners. If it is your first time to use Pytorch, I recommend these [awesome tutorials](#references).\n- If you're interested in DeepNLP, I strongly recommend you to work with this awesome lecture.\n\n  * \u003ca href=\"http://web.stanford.edu/class/cs224n/syllabus.html\"\u003ecs-224n-slides\u003c/a\u003e\n  * \u003ca href=\"https://www.youtube.com/watch?v=OQQ-W_63UgQ\u0026list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6\"\u003ecs-224n-videos\u003c/a\u003e\n\nThis material is not perfect but will help your study and research:) Please feel free to pull requests!!\n\n\u003chr\u003e\n\n## Contents\n\n| Model      | Links   |\n| ------------- |:-------------:| \n| 01. \u003cstrong\u003eSkip-gram-Naive-Softmax\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/01.Skip-gram-Naive-Softmax.ipynb\"\u003enotebook\u003c/a\u003e / data / \u003ca href=\"https://arxiv.org/abs/1301.3781\"\u003epaper\u003c/a\u003e] |\n| 02. \u003cstrong\u003eSkip-gram-Negative-Sampling\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/02.Skip-gram-Negative-Sampling.ipynb\"\u003enotebook\u003c/a\u003e / data / \u003ca href=\"http://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf\"\u003epaper\u003c/a\u003e] |\n| 03. \u003cstrong\u003eGloVe\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/03.GloVe.ipynb\"\u003enotebook\u003c/a\u003e / data / \u003ca href=\"https://nlp.stanford.edu/pubs/glove.pdf\"\u003epaper\u003c/a\u003e] |\n| 04. \u003cstrong\u003eWindow-Classifier-for-NER\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/04.Window-Classifier-for-NER.ipynb\"\u003enotebook\u003c/a\u003e / data / paper] |\n| 05. \u003cstrong\u003eNeural-Dependancy-Parser\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/05.Neural-Dependancy-Parser.ipynb\"\u003enotebook\u003c/a\u003e / \u003ca href=\"https://github.com/rguthrie3/DeepDependencyParsingProblemSet/tree/master/data\"\u003edata\u003c/a\u003e / \u003ca href=\"http://cs.stanford.edu/people/danqi/papers/emnlp2014.pdf\"\u003epaper\u003c/a\u003e] |\n| 06. \u003cstrong\u003eRNN-Language-Model\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/06.RNN-Language-Model.ipynb\"\u003enotebook\u003c/a\u003e / \u003ca href=\"https://github.com/tomsercu/lstm/tree/master/data\"\u003edata\u003c/a\u003e / \u003ca href=\"https://arxiv.org/pdf/1504.00941.pdf\"\u003epaper\u003c/a\u003e] |\n| 07. \u003cstrong\u003eNeural-Machine-Translation-with-Attention\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/07.Neural-Machine-Translation-with-Attention.ipynb\"\u003enotebook\u003c/a\u003e / \u003ca href=\"http://www.manythings.org/anki/\"\u003edata\u003c/a\u003e / \u003ca href=\"https://arxiv.org/pdf/1409.0473.pdf\"\u003epaper\u003c/a\u003e] |\n| 08. \u003cstrong\u003eCNN-for-Text-Classification\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/08.CNN-for-Text-Classification.ipynb\"\u003enotebook\u003c/a\u003e / \u003ca href=\"http://cogcomp.org/Data/QA/QC\"\u003edata\u003c/a\u003e / \u003ca href=\"http://www.aclweb.org/anthology/D14-1181\"\u003epaper\u003c/a\u003e] |\n| 09. \u003cstrong\u003eRecursive-NN-for-Sentiment-Classification\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/09.Recursive-NN-for-Sentiment-Classification.ipynb\"\u003enotebook\u003c/a\u003e / \u003ca href=\"https://nlp.stanford.edu/sentiment/index.html\"\u003edata\u003c/a\u003e / \u003ca href=\"https://nlp.stanford.edu/~socherr/EMNLP2013_RNTN.pdf\"\u003epaper\u003c/a\u003e] |\n| 10. \u003cstrong\u003eDynamic-Memory-Network-for-Question-Answering\u003c/strong\u003e | [\u003ca href=\"https://nbviewer.jupyter.org/github/DSKSD/DeepNLP-models-Pytorch/blob/master/notebooks/10.Dynamic-Memory-Network-for-Question-Answering.ipynb\"\u003enotebook\u003c/a\u003e / \u003ca href=\"https://research.fb.com/downloads/babi/\"\u003edata\u003c/a\u003e / \u003ca href=\"https://arxiv.org/abs/1506.07285\"\u003epaper\u003c/a\u003e] |\n\n\n## Requirements\n\n- Python 3.5\n- Pytorch 0.2+\n- nltk 3.2.2\n- gensim 2.2.0\n- sklearn_crfsuite\n\n\n## Getting started\n\n`git clone https://github.com/DSKSD/cs-224n-Pytorch.git`\n\n### prepare dataset\n\n````\ncd script\nchmod u+x prepare_dataset.sh\n./prepare_dataset.sh\n````\n\n### docker env\nubuntu 16.04 python 3.5.2 with various of ML/DL packages including tensorflow, sklearn, pytorch\n\n`docker pull dsksd/deepstudy:0.2`\n\n````\npip3 install docker-compose\ncd script\ndocker-compose up -d\n````\n\n### cloud setting\n\n`not yet`\n\n## References\n\n* \u003ca href=\"https://github.com/spro/practical-pytorch\"\u003epractical-pytorch\u003c/a\u003e\n* \u003ca href=\"https://github.com/rguthrie3/DeepLearningForNLPInPytorch\"\u003eDeepLearningForNLPInPytorch\u003c/a\u003e\n* \u003ca href=\"https://github.com/yunjey/pytorch-tutorial\"\u003epytorch-tutorial\u003c/a\u003e\n* \u003ca href=\"https://github.com/pytorch/examples/\"\u003epytorch-examples\u003c/a\u003e\n\n## Author\n\nSungdong Kim / \u003ca href=\"https://github.com/DSKSD\"\u003e@DSKSD\u003c/a\u003e","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdsksd%2Fdeepnlp-models-pytorch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdsksd%2Fdeepnlp-models-pytorch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdsksd%2Fdeepnlp-models-pytorch/lists"}