sentence-transformers How to use agraharr/telecom-bge-base-matryoshka with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("agraharr/telecom-bge-base-matryoshka")
sentences = [
"Why is there a specific requirement for maximum uplink transmission timing difference in asynchronous EN-DC configurations?",
"The bandwidth combination set defines the specific arrangements and allowances for channel bandwidths across different NR bands in carrier aggregation configurations. For example, in the case of the CA_n2A-n5A-n48A configuration, the bandwidth combination set is set to 0, indicating that only the specified bandwidths of 5, 10, 15, and 20 MHz can be utilized without any further combinations. This structure ensures that operators can optimize their resources while adhering to technical constraints, leading to improved network efficiency and performance.<|im_end|>",
"The specific requirement for maximum uplink transmission timing difference in asynchronous EN-DC configurations is crucial for ensuring reliable and efficient communication between the User Equipment (UE) and the network. Variations in timing can lead to synchronization issues, impacting the quality of service and data transmission. By defining these timing differences based on various sub-carrier spacings, the specification aims to optimize the performance of the network while accommodating different configurations, ensuring that the UE can handle the complexities of multi-band operation without significant degradation in service quality.<|im_end|>",
"2. Integrity protection"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
