How to use AsaKal/final_sbert_model_e10_bs32_lr0001 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AsaKal/final_sbert_model_e10_bs32_lr0001") sentences = [ "This section understands models related to cybersecurity protects digital systems. Further, it optimizes various threats aspects.", "[LO] Students will be able to design and implement relational database schemas.", "This section implements projects related to quantum computing holds immense promise. Further, it develops various concepts aspects.", "This section develops models related to machine learning algorithms improve constantly. Further, it analyzes various models aspects." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
