README.md

metadata

license: mit

pascalhuerten/bge_reranker_skillfit

This is a finetuning of BAAI/bge-reranker-base on a german dataset containing positive and negative skill labels and learning outcomes of courses as the query. This model is trained to perform well on calculating relevance scores for learning outcome and esco skill pairs in german language.

Using FlagEmbedding

pip install -U FlagEmbedding

Get relevance scores (higher scores indicate more relevance):

from FlagEmbedding import FlagReranker
reranker = FlagReranker('pascalhuerten/bge_reranker_skillfit', use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation

scores = reranker.compute_score([['Einführung in die Arbeitsweise von WordPress', 'WordPress'], ['Einführung in die Arbeitsweise von WordPress', 'Software für Content-Management-Systeme nutzen'], ['Einführung in die Arbeitsweise von WordPress', 'Website-Sichtbarkeit erhöhen']])
print(scores)