How to use deepali1021/finetuned_arctic_ft with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("deepali1021/finetuned_arctic_ft") sentences = [ "What initiatives were implemented in the past year to improve communication between departments?", "with other departments. In the past year, we conducted monthly departmental meetings and \nestablished communication channels to facilitate information sharing and problem-solving. \n \nFare Collection and Fee Structure", "Our fare collection system ensures fair and consistent fee collection from passengers. The current fee \nstructure is as follows: \n \nRegular fare: $2.50 \nSenior citizens and students: $1.50 \nChildren under 5 years old: Free \nFee collection is primarily done through electronic payment methods, such as smart cards and \nmobile payment apps. Drivers are responsible for ensuring correct fare collection and providing \nreceipts upon request. \nRoute Information and Rules \nOur transportation department operates multiple routes within the city. Route information, including \nmaps, schedules, and stops, is available on our website and at designated information centers.", "Our drivers are responsible for operating vehicles safely, following traffic rules and regulations. They \nare required to hold a valid driver's license and maintain a clean driving record. In the past year, our \ndrivers completed over 2,000 hours of driving training to enhance their skills and knowledge. \n \nRoute Planning and Optimization \nEfficient route planning is essential for timely transportation services. Our department utilizes \nadvanced routing software to optimize routes and minimize travel time. In the past year, we reduced \nour average route duration by 15% through effective route planning and optimization strategies. \n \nCustomer Service" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
