Is it possible to use Gliner with at token level instead of text?
#2
by
polodealvarado
- opened
Hello @urchade !
Thank you for such amazing model.
I would like to know if it is possible to run it at token level (list of words) instead of using directly a text.
Something like:
model.predict_entities(["Albert","is","living","in","Paris","."], labels = ["person name","location"])
Hi @polodealvarado , you can joint you token lists with whitespace and use a whitespace splitter for tokenization
model.words_splitter = WordsSplitter("whitespace")
text = " ".join(["Albert","is","living","in","Paris","."])
Sorry for replying late.
Thank you
@urchade
!
polodealvarado
changed discussion status to
closed