What are the best practices for sharing fine-tuned models and their associated metadata?

Jan 25, 2024 ... Learn Machine Learning. Welcome to r/learnmachinelearning - a community of learners and educators passionate about machine learning! This is ... Feb 13, 2025 ... Fine-tuning is a form of transfer learning where the pre-trained model is adjusted to better fit the new data. There are several steps involved ... Fine-Tuning in Modern Machine Learning: Principles and Scalability. Fanghui Liu, Grigorios Chrysos, Beidi Chen, Rebekka Burkholz, Saleh Soltan, Angeliki ... Sep 27, 2023 ... Fine-tuning is a technique used in deep learning to enhance pre-trained models and improve their performance at specific tasks. Fine-tuning ... Feb 13, 2025 ... Fine-tuning is a powerful technique in machine learning, allowing pre-trained models to be adapted to specific tasks with minimal computational cost. Deep learning practice is increasingly driven by powerful foundation models (FM), pre-trained at scale and then fine-tuned for specific tasks of interest. Aug 30, 2018 ... How a TPU works. When Google designed the TPU, we built a domain-specific architecture. That means, instead of designing a general purpose ... Oct 31, 2024 ... Exx-Blog-5-Tips-for-Fine-Tuning-LLMs. Deep Learning. Top 5 Tips for Fine-Tuning LLMs. October 31, 2024 11 min read. Why Fine-Tuning Matters? Modifying the "initial_epoch" arg when doing fine tuning and transfer learning. ... mrdbourke / tensorflow-deep-learning Public. Notifications You must be signed ... We present GOODFIT, one of the first optimizers that has been specifically designed to operate on converged models that need to be incrementally fine-tuned ...