[](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/ChemNLP_Example.ipynb)
[](https://zenodo.org/badge/latestdoi/523320947)
# ChemNLP
# Table of Contents
* [Introduction](#intro)
* [Installation](#install)
* [Examples](#example)
* [Web-app](#webapp)
* [Reference](#reference)
<a name="intro"></a>
Introduction
-------------------------
ChemNLP is a software-package to process chemical information from the scientific literature.
<a name="install"></a>
Installation
-------------------------
First create a conda environment:
Install miniconda environment from https://conda.io/miniconda.html
Based on your system requirements, you'll get a file something like 'Miniconda3-latest-XYZ'.
Now,
```
bash Miniconda3-latest-Linux-x86_64.sh (for linux)
bash Miniconda3-latest-MacOSX-x86_64.sh (for Mac)
```
Download 32/64 bit python 3.8 miniconda exe and install (for windows)
Now, let's make a conda environment, say "chemnlp", choose other name as you like::
```
conda create --name chemnlp python=3.8
source activate chemnlp
```
#### Method 1 (using setup.py):
Now, let's install the package:
```
git clone https://github.com/usnistgov/chemnlp.git
cd chemnlp
python setup.py develop
cde data download
```
#### Method 2 (using pypi):
As an alternate method, ChemNLP can also be installed using `pip` command as follows:
```
pip install chemnlp
cde data download
```
<a name="example"></a>
Examples
---------
#### Parse chemical formula
```
run_chemnlp.py --file_path="chemnlp/tests/XYZ"
```
#### Text classification example
```
python chemnlp/classification/scikit_class.py --csv_path chemnlp/sample_data/cond_mat_small.csv
```
[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)
[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)
<a name="webapp"></a>
Using the webapp
---------
The webapp is available at: https://jarvis.nist.gov/jarvischemnlp
<a name="reference"></a>
Reference
---------
[ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text Data](https://arxiv.org/abs/2209.08203)
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