sentence-transformers How to use dinho1597/bge-small-qa-telecom-ft with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("dinho1597/bge-small-qa-telecom-ft")
sentences = [
"What property is denoted as the M→M property in the queueing network literature?",
"The LOFAR system introduces two additional levels in the beam hierarchy: the compound (tile) beam and the station beam.",
"The desired pseudonoise sequence in a CDMA system has the characteristics that the fraction of 0's and 1's is almost half-and-half over the period, and the shifted versions of the pseudonoise sequence are nearly orthogonal to each other. If the shift of the pseudonoise sequence is randomized, it becomes a random process.",
"The M→M property in the queueing network literature denotes the independence of individual queues in the long term."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
