How to use Corran/SciGenNomicEmbedStaticOnnx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Corran/SciGenNomicEmbedStaticOnnx") sentences = [ "Stating purpose of the current research with reference to gaps or issues in the literature", "During the 15-year study, 10% of the osseointegrated implants in the edentulous jaw showed signs of peri-implantitis, leading to their failure.", "This paper provides an in-depth exploration of the qualitative case study methodology, addressing the lack of comprehensive guidance for novice researchers in this area.", "As a novice researcher in management science, I have been drawn to the qualitative case study methodology due to its ability to provide rich, in-depth insights into complex real-world situations." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
