The use of *Offline* #FOSS #NaturalLanguageProcessing and models (aka #LLMs) have always intrigued me.
Learn how to use #KeyBERT #KeyphraseVectorizers (made possible by the awesome #spaCy models) to enhance Markdown blogposts with automatically generated keywords.
https://www.spdevalk.nl/blog/post-adding-key-phrases-to-jekyll-blog-posts-_-the-offline-edition/
Still slowly working on the #keyword extraction and storage in #json file.
I didn't manage to enable #stopwords in #keyBERT, so the plan is to filter the keywords in additional step.
The "#WordPress" or "plugin" keyword for each plugin would be useless.
The next step that follows will be to find #synonyms for each keyword... and I think I'll be using NLTK #wordNet in #python. Not sure if it's the best option.
12/:bongoCat:
I've tested out keyword extraction using #keyBert, and it looks promising - more so than any #javaScript package I came across before.
It took around 10-15 minutes to install all of the dependencies of the package. It reported no warnings or errors in the #terminal.
I was pleasantly surprised that you can run/test out #python code inside of the #vsCode editor with a one simple click.
I still need to get used to difference in #dataTypes compared to #php & #js.
9/:bongoCat:
