How to use dnth/ssf-retriever-modernbert-embed-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dnth/ssf-retriever-modernbert-embed-base") sentences = [ "The Warehouse Operations Executive/Inventory Management Executive/Warehouse Assistant Manager is responsible for planning and implementing complex warehouse processes, operations and technology. He/She is also responsible for developing plans to monitor and optimise storage utilisation levels, implementing quality programmes and using data analytics to review efficiency of the warehouse storage and layout plans. Analytical and logical, he is required to explore solutions and analyse the feasibility of plans. He is also expected to coordinate closely with internal and external stakeholders to implement processes and technology, and to assist in the management of the warehouse operations department.", "Warehouse Operations Manager responsible for overseeing and optimizing warehouse processes, managing inventory systems, and utilizing data analytics to enhance storage efficiency and layout. This role involves collaboration with various stakeholders to implement effective operational strategies and maintain quality standards.", "Lead Social Worker responsible for developing intervention plans, delivering training, and evaluating programs within the organization while collaborating with various communities and agencies.", "Junior Risk Analyst needed in the finance sector to support the evaluation and mitigation of potential risks within investment portfolios. The role includes conducting thorough risk assessments, preparing reports, and collaborating with senior analysts to enhance risk management frameworks. Strong analytical skills and familiarity with financial regulations are essential." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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