sentence-transformers How to use datasocietyco/bge-base-en-v1.5-course-recommender-v4python with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("datasocietyco/bge-base-en-v1.5-course-recommender-v4python")
sentences = [
"Fundamentals of Deep Learning for Multi GPUs. Find out how to use multiple GPUs to train neural networks and effectively parallelize\\ntraining of deep neural networks using TensorFlow.. tags: multiple GPUs, neural networks, TensorFlow, parallelize. Languages: Course language: Python. Prerequisites: No prerequisite course required. Target audience: Professionals want to train deep neural networks on multi-GPU technology to shorten\\nthe training time required for data-intensive applications.",
"Course Name:Hypothesis Testing in Python|Course Description:In this course, learners with foundational knowledge of statistical concepts will dive deeper into hypothesis testing by focusing on three standard tests of statistical significance: t-tests, F-tests, and chi-squared tests. Covering topics such as t-value, t-distribution, chi-square distribution, F-statistic, and F-distribution, this course will familiarize learners with techniques that will enable them to assess normality of data and goodness-of-fit and to compare observed and expected frequencies objectively.|Tags:f-distribution, chi-square distribution, f-statistic, t-distribution, t-value|Course language: Python|Target Audience:Professionals some Python experience who would like to expand their skill set to more advanced Python visualization techniques and tools.|Prerequisite course required: Foundations of Statistics in Python",
"Course Name:Foundations of Data & AI Literacy for Managers|Course Description:Designed for managers leading teams and projects, this course empowers individuals to build data-driven organizations and integrate AI tools into daily operations. Learners will gain a foundational understanding of data and AI concepts and learn how to leverage them for actionable business insights. Managers will develop the skills to increase collaboration with technical experts and make informed decisions about analysis methods, ensuring their enterprise thrives in today’s data-driven landscape.|Tags:Designed, managers, leading, teams, projects,, course, empowers, individuals, build, data-driven, organizations, integrate, AI, tools, into, daily, operations., Learners, will, gain, foundational, understanding, data, AI, concepts, learn, how, leverage, them, actionable, business, insights., Managers, will, develop, skills, increase, collaboration, technical, experts, make, informed, decisions, about, analysis, methods,, ensuring, their, enterprise, thrives, today’s, data-driven, landscape.|Course language: None|Target Audience:No target audience|No prerequisite course required",
"Course Name:Fundamentals of Deep Learning for Multi GPUs|Course Description:Find out how to use multiple GPUs to train neural networks and effectively parallelize\\ntraining of deep neural networks using TensorFlow.|Tags:multiple GPUs, neural networks, TensorFlow, parallelize|Course language: Python|Target Audience:Professionals want to train deep neural networks on multi-GPU technology to shorten\\nthe training time required for data-intensive applications|No prerequisite course required"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
