How to use noystl/recomb-pred-bge-large-en with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("noystl/recomb-pred-bge-large-en") sentences = [ "Represent this sentence for searching relevant passages: Existing methods for anomaly detection on dynamic graphs struggle with capturing complex time information in graph structures and generating effective negative samples for unsupervised learning. These challenges highlight the need for improved methodologies that can address the limitations of current approaches in this field.We suggest combining 'a message-passing framework' and ", "a single global model", "videos", "sequential polygon generation" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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