I have my own data set consisting a a few hundred abstracts and I want to see baseline performance using Sci-BERT's PICO functionality. Are there code snip bits for easily running inference on your own dataset and just seeing how it classifies? I tried to use the huggingface models and the AWS deploy code but Im not sure how to use if for a PICO task, let alone interpret the text classification outputs it gives, which just seem to be "LABEL_0" or "LABEL_1". Any help on this would be much appreciated!
I have my own data set consisting a a few hundred abstracts and I want to see baseline performance using Sci-BERT's PICO functionality. Are there code snip bits for easily running inference on your own dataset and just seeing how it classifies? I tried to use the huggingface models and the AWS deploy code but Im not sure how to use if for a PICO task, let alone interpret the text classification outputs it gives, which just seem to be "LABEL_0" or "LABEL_1". Any help on this would be much appreciated!