How to use saraleivam/GURU-paraphrase-multilingual-MiniLM-L12-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("saraleivam/GURU-paraphrase-multilingual-MiniLM-L12-v2") sentences = [ "Reportando a Mánager ventasLograr un crecimiento sostenible de los ingresos mediante la negociación, cierre, implementación y cumplimiento de acuerdos con los diferentes clientes.Encargado de realizar la búsqueda y apertura de nuevos clientes a nivel LATAM . Entender requerimientos y saber asesorar de la mejor manera para un buen cierre de negocio. Alto conocimiento en la línea de flotas y Camiones.", "Modernize Infrastructure and Applications with Google Cloud.Data Science.Business Strategy.Understand the role that cloud modernization and migration plays in an organization's digital transformation.. Examine available options to run compute workloads in the cloud.. Explore the advantages of using containers, serverless computing, and APIs in application modernization.. Learn about the business reasons to choose hybrid or multi-cloud strategies, and how GKE Enterprise can help support these strategies.", "Microsoft 365 Copilot for Leaders.Data Science.Machine Learning.Risk Management", "Decoding AI: A Deep Dive into AI Models and Predictions.Data Science.Machine Learning.Learn key concepts and terminology in artificial intelligence (AI), including machine learning, generative AI, and deep learning . Learn the core components of machine learning systems, including data, models, and evaluation techniques. Recognize why AI systems can fail and identify the kinds of work required to make useful technology. Identify common pitfalls in conversations about AI and recognize conflicts of interest when interpreting claims about AI systems" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
