This is an open collection of methodologies, tools and step by step instructions to help with successful training and fine-tuning of large language models and multi-modal models and their inference.
Dot Physics on MSN
Python physics tutorial: Modeling 1D motion with loops
Learn how to model 1D motion in Python using loops! ๐โ๏ธ This step-by-step tutorial shows you how to simulate position, velocity, and acceleration over time with easy-to-follow Python code. Perfect ...
Dot Physics on MSN
Learn Python for physics lesson 1: Hello world and variables
Master the right-hand rule in physics with this easy-to-follow tutorial! In this video, we explain how to use the right-hand rule correctly to determine directions of magnetic fields, currents, and ...
Machine learning is an essential component of artificial intelligence. Whether itโs powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
Abstract: According to the World Health Organization (WHO), some chronic diseases such as diabetes mellitus, stroke, cancer, cardiac vascular, kidney failure, and hypertension are essential for early ...
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