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Optimum: Accelerate Hugging Face Models with Hardware Optimization
Optimum is an extension of Hugging Face Transformers, Diffusers, TIMM, and Sentence-Transformers, designed to provide a suite of optimization tools. It enables maximum efficiency for training and running models on targeted hardware, simplifying the process for developers. This library helps users achieve significant performance gains across various machine learning workflows.
multiresolution-time-series-transformer: Long-term Forecasting with MTST
This repository provides a PyTorch implementation of the Multi-Resolution Time-Series Transformer (MTST) for long-term forecasting. Based on the Zhang et al. (2024) paper, MTST processes temporal data at different resolutions to effectively capture both short-term and long-term patterns. It offers a flexible and robust solution for advanced time series prediction tasks.