sentence-transformers How to use Corran/SciTopicNomicEmbed with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Corran/SciTopicNomicEmbed", trust_remote_code=True)
sentences = [
"Despite the crucial role of phosphorus in global food production, there is a lack of comprehensive analysis on the economic and policy aspects of phosphorus supply and demand, highlighting a significant knowledge gap in the field of natural resource economics.",
"The human brain is intrinsically organized into dynamic, anticorrelated functional networks",
"The story of phosphorus: Global food security and food for thought",
"Identifying a knowledge gap in the field of study"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
