{ "info": { "author": "Alexandra Institute", "author_email": "dansknlp@alexandra.dk", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: BSD License", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3 :: Only", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Artificial Intelligence" ], "description": "

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\n \n Models\n \n | \n \n Datasets\n \n | \n \n Examples\n \n

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\nDaNLP is a repository for Natural Language Processing resources for the Danish Language. \nIt is a collection of available datasets and models for a variety of NLP tasks.\nIt features code examples on how to use the datasets and models in popular NLP frameworks such as spaCy and Flair as well as Deep Learning frameworks such as PyTorch and TensorFlow.\n\n**News**\n\n- :mag_right: Name Entity Recognition model trained using Flair is added , [se here](docs/models/ner.md)\n\n- \ud83c\udf89 Version 0.0.3 has been [released](https://github.com/alexandrainst/danlp/releases) with loading functions for Danish NER datasets\n\n- \u2728 The Danish Dependency Treebank has been annotated with NER tags. You can use DaNLP [to load it](docs/datasets.md#danish-dependency-treebank)\n\n\n\n**Next up**\n\n- \ud83d\udea7 Improved models trained on the new annotated [Danish NER dataset](docs/datasets.md#danish-dependency-treebank)\n- \ud83d\udea7 Support for Danish in the [spaCy](https://github.com/explosion/spaCy) framework\n\n\n\n## Get started\n\nTo get started using DaNLP in your python project simply install the pip package. However installing the pip package \nwill not install all NLP libraries. If you want to try out the models in DaNLP you can use the Docker images\nthat has all the NLP libraries installed.\n\n### Install with pip\nTo get started using DaNLP simply install the project with pip:\n\n```bash\npip install danlp\n```\n\nNote that the installation of DaNLP does not install other NLP libraries such as Gensim, Spacy or Flair.\nThis allows the installation to be as minimal as possible and let the user choose to e.g. load word embeddings with either spaCy, flair or Gensim. Therefore, depending on the function you need to use, you should install one or several of the following: `pip install flair`, `pip install spacy ` or/and `pip install gensim `.\n\n### Install with Docker \nTo quickly get started with DaNLP and to try out the models you can use our Docker image.\nTo start a ipython session simply run:\n```bash\ndocker run -it --rm alexandrainst/danlp ipython\n```\nIf you want to run a `` in your current working directory you can run:\n```bash\ndocker run -it --rm -v \"$PWD\":/usr/src/app -w /usr/src/app alexandrainst/danlp python \n```\nYou can also quickly get started with one of our [notebooks](/examples).\n \u200b \n\n\n## NLP Models\nNatural Language Processing is an active area of research and it consists of many different tasks. \nThe DaNLP repository provides an overview of Danish models for some of the most common NLP tasks.\n\nThe repository is under development and this is the list of NLP tasks we have covered and plan to cover in the repository.\n- [x] [Embedding of text](docs/models/embeddings.md)\n- [x] [Part of speech](docs/models/pos.md)\n- [x] [Named Entity Recognition](docs/models/ner.md)\n- [x] [Sentiment Analysis](docs/models/sentiment_analysis.md)\n- [ ] Coreference resolution\n\nIf you are interested in Danish support for any specific NLP task you are welcome to get in contact with us.\n\n## Datasets\nThe number of datasets in the Danish is limited. The DaNLP repository provides an overview of the available Danish datasets that can be used for commercial purposes.\n\nThe DaNLP package allows you to download and preprocess datasets. You can read about the datasets [here](/docs/datasets.md).\n\n## Examples\nYou will find examples and tutorials [here](/examples) that shows how to use NLP in Danish. This project keeps a Danish written [blog](https://medium.com/danlp) on medium where we write about Danish NLP, and in time we will also provide some real cases of how NLP is applied in Danish companies.\n\n## How do I contribute?\n\nIf you want to contribute to the DaNLP repository and make it better, your help is very welcome. You can contribute to the project in many ways:\n\n- Help us write good tutorials on Danish NLP use-cases\n- Contribute with your own pretrained NLP models or datasets in Danish\n- Notify us of other Danish NLP resources\n- Create GitHub issues with questions and bug reports\n\n## Who is behind?\n\n\nThe DaNLP repository is maintained by the [Alexandra Institute](https://alexandra.dk/uk) which is a Danish non-profit company \nwith a mission to create value, growth and welfare in society. The Alexandra Institute is a member of [GTS](https://gts-net.dk/), \na network of independent Danish research and technology organisations.\n\nThe work on this repository is part the [Dansk For Alle](https://bedreinnovation.dk/dansk-alle-0) performance contract \nallocated to the Alexandra Insitute by the [Danish Ministry of Higher Education and Science](https://ufm.dk/en?set_language=en&cl=en). The project runs in two years in 2019 and 2020, and an overview of the project can be found on our [microsite](https://danlp.alexandra.dk/). \n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/alexandrainst/danlp/", "keywords": "", "license": "BSD 3-Clause License", "maintainer": "", "maintainer_email": "", "name": "danlp", "package_url": "https://pypi.org/project/danlp/", "platform": "", "project_url": "https://pypi.org/project/danlp/", "project_urls": { "Homepage": "https://github.com/alexandrainst/danlp/" }, "release_url": "https://pypi.org/project/danlp/0.0.4/", "requires_dist": [ "tqdm", "pyconll" ], "requires_python": "", "summary": "DaNLP: NLP in Danish", "version": "0.0.4" }, "last_serial": 5995389, "releases": { "0.0.1": [ { "comment_text": "", "digests": { "md5": "3d164c2707037ffcea536507aa2ea171", "sha256": "92d393ab6e13e89041382325d0e015153a756562f29247fa55bdc1261a8d7390" }, "downloads": -1, "filename": "danlp-0.0.1-py3-none-any.whl", "has_sig": false, "md5_digest": "3d164c2707037ffcea536507aa2ea171", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 12504, "upload_time": "2019-07-16T13:26:04", "url": "https://files.pythonhosted.org/packages/41/a5/6bbd51a93fd05f27a610cbb4e631b4931ed1ed81661d08cdc43184202567/danlp-0.0.1-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "57c4e93e6fb11d20ed8556b27680c4f2", "sha256": "910e3280ebe0c663c27fba345176baa5fceee4df40fd4b255e7da66e496e9a26" }, "downloads": -1, "filename": "danlp-0.0.1.tar.gz", "has_sig": false, "md5_digest": "57c4e93e6fb11d20ed8556b27680c4f2", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10717, "upload_time": "2019-07-16T13:26:06", "url": "https://files.pythonhosted.org/packages/0e/f8/4db1f8e47bb12c50b773217a5e9d9751dd97fa7eb42411d63a4cc85b1c93/danlp-0.0.1.tar.gz" } ], "0.0.2": [ { "comment_text": "", "digests": { "md5": "ccf661f406a1bf9c15d024758a4afcf2", "sha256": "8c7c898d20a46754ad258855c623850d660069c687b5b8c877d35feafa97e411" }, "downloads": -1, "filename": "danlp-0.0.2-py3-none-any.whl", "has_sig": false, "md5_digest": "ccf661f406a1bf9c15d024758a4afcf2", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 13253, "upload_time": "2019-07-24T14:21:44", "url": "https://files.pythonhosted.org/packages/6d/16/3b741a434e373857dcfa331d875c59e70673323b45dd79e75a4166f4ac99/danlp-0.0.2-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "cc930104fefd60e1ad9c50387f3440eb", "sha256": "cb08078741019da938fe2b0d2dadd5ba5e72efa37b537191ad4c4dee647b3821" }, "downloads": -1, "filename": "danlp-0.0.2.tar.gz", "has_sig": false, "md5_digest": "cc930104fefd60e1ad9c50387f3440eb", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11153, "upload_time": "2019-07-24T14:21:47", "url": "https://files.pythonhosted.org/packages/c8/ac/947e69676e022e407907b70aa0af22b5d29166a6c580c724f733c080a37a/danlp-0.0.2.tar.gz" } ], "0.0.3": [ { "comment_text": "", "digests": { "md5": "f2554ee8c694aa0c3e4f3337976728ae", "sha256": "6c330028d9e772d4e6632aa138236ac1366dfb7fd66c284beba773020cb5487c" }, "downloads": -1, "filename": "danlp-0.0.3-py3-none-any.whl", "has_sig": false, "md5_digest": "f2554ee8c694aa0c3e4f3337976728ae", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 19639, "upload_time": "2019-10-02T21:29:33", "url": "https://files.pythonhosted.org/packages/dd/4d/3137b6ee023a971af35d2be0d5f05eb91a48bbb073c3f0d8c4cc27b865df/danlp-0.0.3-py3-none-any.whl" } ], "0.0.4": [ { "comment_text": "", "digests": { "md5": "250e9d89801b1523f69abf347f98f3d1", "sha256": "95792c08d45bcc5ee4bc0f68364346db5dda16a93014452c0edc17e3ee3dec79" }, "downloads": -1, "filename": "danlp-0.0.4-py3-none-any.whl", "has_sig": false, "md5_digest": "250e9d89801b1523f69abf347f98f3d1", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 20841, "upload_time": "2019-10-18T12:30:09", "url": "https://files.pythonhosted.org/packages/8d/f4/475b0f6a6b7c48b29c8704481701b1ea2de890aaebd8706397bcb4701572/danlp-0.0.4-py3-none-any.whl" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "250e9d89801b1523f69abf347f98f3d1", "sha256": "95792c08d45bcc5ee4bc0f68364346db5dda16a93014452c0edc17e3ee3dec79" }, "downloads": -1, "filename": "danlp-0.0.4-py3-none-any.whl", "has_sig": false, "md5_digest": "250e9d89801b1523f69abf347f98f3d1", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 20841, "upload_time": "2019-10-18T12:30:09", "url": "https://files.pythonhosted.org/packages/8d/f4/475b0f6a6b7c48b29c8704481701b1ea2de890aaebd8706397bcb4701572/danlp-0.0.4-py3-none-any.whl" } ] }