{"id":14816819,"url":"https://github.com/usnistgov/chemnlp","last_synced_at":"2025-09-16T21:32:30.697Z","repository":{"id":57747639,"uuid":"523320947","full_name":"usnistgov/chemnlp","owner":"usnistgov","description":"ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text 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Models"],"sub_categories":[],"readme":"[![name](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ChemNLP_Example.ipynb)\n![alt text](https://github.com/usnistgov/chemnlp/actions/workflows/main.yml/badge.svg)\n[![DOI](https://zenodo.org/badge/523320947.svg)](https://zenodo.org/badge/latestdoi/523320947)\n\n\n# ChemNLP\n\n# Table of Contents\n* [Introduction](#intro)\n* [Installation](#install)\n* [Examples](#example)\n* [Web-app](#webapp)\n* [Reference](#reference)\n\n\u003ca name=\"intro\"\u003e\u003c/a\u003e\nIntroduction\n-------------------------\nChemNLP is a software-package to process chemical information from the scientific literature.\n\n\u003cp align=\"center\"\u003e\n   \u003cimg src=\"https://github.com/usnistgov/chemnlp/blob/develop/chemnlp/Schemcatic.PNG\" alt=\"ChemNLP\"  width=\"600\"/\u003e\n\u003c/p\u003e\n\n\u003ca name=\"install\"\u003e\u003c/a\u003e\nInstallation\n-------------------------\nFirst create a conda environment:\nInstall miniconda environment from https://conda.io/miniconda.html\nBased on your system requirements, you'll get a file something like 'Miniconda3-latest-XYZ'.\n\nNow,\n\n```\nbash Miniconda3-latest-Linux-x86_64.sh (for linux)\nbash Miniconda3-latest-MacOSX-x86_64.sh (for Mac)\n```\nDownload 32/64 bit python 3.8 miniconda exe and install (for windows)\nNow, let's make a conda environment, say \"chemnlp\", choose other name as you like::\n```\nconda create --name chemnlp python=3.9\nsource activate chemnlp\n```\n#### Method 1 (using setup.py):\n\nNow, let's install the package:\n```\ngit clone https://github.com/usnistgov/chemnlp.git\ncd chemnlp\npython setup.py develop\ncde data download\n```\n\n#### Method 2 (using pypi):\n\nAs an alternate method, ChemNLP can also be installed using `pip` command as follows:\n```\npip install chemnlp\ncde data download\n```\n\n\u003ca name=\"example\"\u003e\u003c/a\u003e\nExamples\n---------\n#### Parse chemical formula \n\n```\nrun_chemnlp.py --file_path=\"chemnlp/tests/XYZ\"\n```\n\n#### Text classification example\n\n```\npython chemnlp/classification/scikit_class.py --csv_path chemnlp/sample_data/cond_mat_small.csv\n```\n\n[Google Colab example for installation and text classification](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ChemNLP_Example.ipynb)\n\n#### Text generation example\n\n[Google Colab example for Text Generation with HuggingFace](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ChemNLP_TitleToAbstract.ipynb)\n\n\n\u003ca name=\"webapp\"\u003e\u003c/a\u003e\nUsing the webapp\n---------\nThe webapp is available at: https://jarvis.nist.gov/jarvischemnlp\n\n![JARVIS-ChemNLP](https://github.com/usnistgov/chemnlp/blob/develop/chemnlp/PTable.PNG)\n\n\u003ca name=\"reference\"\u003e\u003c/a\u003e\nReference\n---------\n\n1. [ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text Data](https://github.com/usnistgov/chemnlp)\n2. [AtomGPT: Atomistic Generative Pretrained Transformer for Forward and Inverse Materials Design](https://pubs.acs.org/doi/full/10.1021/acs.jpclett.4c01126)\n3. [JARVIS-Leaderboard](https://pages.nist.gov/jarvis_leaderboard)\n4. [NIST-JARVIS Infrastructure](https://jarvis.nist.gov/)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fusnistgov%2Fchemnlp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fusnistgov%2Fchemnlp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fusnistgov%2Fchemnlp/lists"}