sentence-transformers How to use ShushantLLM/paraphrase-multilingual-mpnet-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("ShushantLLM/paraphrase-multilingual-mpnet-base-v2")
sentences = [
"CBRN defense, predictive analytics, natural language understanding",
"experience with speech interfaces Lead and evaluate changing dialog evaluation conventions, test tooling developments, and pilot processes to support expansion to new data areas Continuously evaluate workflow tools and processes and offer solutions to ensure they are efficient, high quality, and scalable Provide expert support for a large and growing team of data analysts Provide support for ongoing and new data collection efforts as a subject matter expert on conventions and use of the data Conduct research studies to understand speech and customer-Alexa interactions Assist scientists, program and product managers, and other stakeholders in defining and validating customer experience metrics\n\nWe are open to hiring candidates to work out of one of the following locations:\n\nBoston, MA, USA | Seattle, WA, USA\n\nBasic Qualifications\n\n 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience 2+ years of data scientist experience Bachelor's degree Experience applying theoretical models in an applied environment\n\nPreferred Qualifications\n\n Experience in Python, Perl, or another scripting language Experience in a ML or data scientist role with a large technology company Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science\n\nAmazon is committed to a diverse and inclusive workplace. Amazon is \n\nOur compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $111,600/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.\n\n\nCompany - Amazon.com Services LLC\n\nJob ID: A2610750",
"Skills: Your Expertise:\n5+ years in industry experience and a degree (Masters or PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research).Expert communication and collaboration skills with the ability to work effectively with internal teams in a cross-cultural and cross-functional environment. Ability to conduct rigorous analysis and communicate conclusions to both technical and non-technical audiencesExperience partnering with internal teams to drive action and providing expertise and direction on analytics, data science, experimental design, and measurementExperience in analysis of A|B experiments and statistical data analysisExperience designing and building metrics, from conception to building prototypes with data pipelinesStrong knowledge in at least one programming language (Python or R) and in SQLAbility to drive data strategies, with a central source of truth to impact business decisionsKnowledge and experience in insurance industry - a plusKnowledge and experience in customer experience measurement - a plus\nKeywords:Education: Minimum: BS/BA in CS or related field (or self-taught/ equivalent work experience) Preferred: MS/MA in CS or related field",
"requirements of the program or company.\n\n Working across the globe, V2X builds smart solutions designed to integrate physical and digital infrastructure from base to battlefield. We bring 120 years of successful mission support to improve security, streamline logistics, and enhance readiness. Aligned around a shared purpose, our $3.9B company and 16,000 people work alongside our clients, here and abroad, to tackle their most complex challenges with integrity, respect, responsibility, and professionalism. \n\nAt V2X, we are making a difference by delivering decision support tools critical for the protection of our forces when threatened by both physical and Chemical, Biological, Radiological, or Nuclear (CBRN) threats.\n\nWe are expanding in data science to provide the best information possible utilizing the latest techniques in Machine Learning (including Deep Learning, Neural network). We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team. Our data scientists work closely everyday with project managers, subject matter experts and software engineers to work on challenges in machine intelligence, data mining, and machine learning, and work together with agility to build capabilities that impress our customers. We partner and collaborate with universities to being best minds together.\n\nData scientists will have opportunities to work on projects with highest priority to our business. Vital to success in this role is the ability to determine, define and deploy predictive / prescriptive analytic solutions to identify and perform root cause analysis on adverse trends, by choosing best fit methods, defining algorithms, and validating and deploying models to achieve results.\n\nResponsibilities\n\nMajor Job Activities:\n\n Partner with our development teams to solve problems and identify trends and opportunities to leverage data from multiple sources. Collaborate across multiple teams. Passionate about working with large and complex unstructured and structured data sets. Strong communication and interpersonal skills. You should be able to work across functions and effectively present, recommend and communicate a position by demonstrating its value and tradeoffs. Comfortable conducting design, algorithm, and code reviews. Able to self-direct and succeed with minimal guidance. \n\nMaterial & Equipment Directly Used:\n\nComputer, Phone, and basic office materials.\n\nWorking Environment:\n\n Function in an office environment in a stationary position approximately 50 percent of the time or more. Must be able to operate standard office equipment, such as a computer, copy machine, and printer. \n\nQualifications\n\nEducation / Certifications:\n\n Bachelor’s degree in a computer, engineering, or quantitative discipline (e.g., statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering). Master's or Ph.D. in a quantitative discipline preferred. \n\nClearance Requirement: \n\nMust have or be able to obtain an active U.S. DoD Secret (or higher) level Security Clearance.\n\nExperience / Skills:\n\n 5+ years of relevant work experience in data analysis or related field. (e.g., statistician, data analyst, data scientist). Programming experience in one or more of the following: R, MATLAB, C, C++, Java, Python, Scala Experience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence). Experience with statistical software (e.g., R, Octave, Julia, MATLAB, pandas) and database languages (e.g., SQL). Experience with machine learning related open source libraries including, but not limited to: Hadoop, Spark, SciKit-Learn, TensorFlow, etc. Contribution to research communities and/or efforts, including publishing papers at conferences. \n\nWe are committed to an inclusive and diverse workplace that values and supports the contributions of each individual. This commitment along with our common Vision and Values of Integrity, Respect, and Responsibility, allows us to leverage differences, encourage innovation and expand our success in the global marketplace. V2X is an Equal Opportunity /Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, protected veteran status or status as an individual with a disability."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
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