As I said, currently, I am a big fun of AI2. This began when I got knowing its work into an open-source NLP research library - AllenNLP. The more I hack the library, the more attractive it is for me. A short paragraph of praise below was written when I was hacking the tool.

I appreciate how the library strongly reflects the importance of reproducibility and conciseness regarding code design. It is not only a good example of my future code writing but also a motivation for me becoming an excellent researcher with the open-source concept in mind. The tool definitely helps me solve a lot of trivial time-consuming dirty work and enables me to focus on the most important part in research - logic and creative thinking.

If you aspire to be a NLP researcher, this wonderful library is highly recommended as starting point in terms of programing NLP. Anyway, it is a good tool for running reproducible experiments which I think is pretty much important for not only NLP reseachers but researchers in other areas. More about its contribution to reproducibility, the slides by Joel Grus are good references. To start AllenNLP, there are a number of good tutorials available on its git repository page.

Although I have played some time with AllenNLP on Mac OS and Linux, unfortunately, the library is still unavailable for Windows. Especially, it is an important need for me to conduct experiments with AllenNLPdirectly on my GPU-supported Windows. This blog provides a way of making a detour to enable AllenNLP run on Windows. Instructions are below.

Please go to the code repository, where readme file contains all details.

If you have any doubts or any my mistakes you found in the blog, send me an email via wangcongcongcc@gmail.com or you are welcome to talk with me about any NLP relevant questions through my Twitter account.