How to use VaggP/fine-tuned-bge-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VaggP/fine-tuned-bge-large") sentences = [ " The misconception lies in incorrectly aligning decimal points during addition, leading to an improper sum.", "Converts a fraction to a percentage by placing a decimal point between the numerator and denominator", "When two digits sum to 10 or more during an addition problem, does not add one to the preceding digit", "Confuses square rooting and halving the number" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
