sentence-transformers How to use pranamjain/bge-finetuned-rag with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("pranamjain/bge-finetuned-rag")
sentences = [
"What year do the patent families related to DARZALEX expire in the United States?",
"Amortization for owned content predominantly monetized on an individual basis and accrued costs associated with participations and residuals payments are recorded using the individual film forecast computation method, which recognizes the costs in the same ratio as the associated ultimate revenue.",
"The two patent families both expire in the United States in 2029.",
"For the year ended December 31, 2022, net cash used in investing activities of $371.9 million was primarily from the purchase of $247.3 million marketable securities, net of sale and maturities, $62.2 million net cash used to acquire GreenCom, SolarLeadFactory and ClipperCreek, $46.4 million used in purchases of test and assembly equipment to expand our supply capacity, related facility improvements and information technology enhancements, including capitalized costs related to internal-use software and $16.0 million used to invest in private companies."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
