A deep learning-based toolkit for predicting fuel cell voltage curves, built on PyTorch. It supports pre-trained model invocation, training and prediction, gradient tracking, training monitoring, and data post-processing. Compatible with both CPU and GPU clusters, this package provides an efficient solution for fuel cell modeling and analysis. This repository provides a comprehensive software package for predicting fuel cell voltage curves using deep learning. Built on the PyTorch platform, it offers robust support for CPU and GPU clusters. Key features include:
- Efficient invocation of pre-trained models.
- Customizable model training and prediction workflows.
- Gradient tracking for insightful model analysis.
- Real-time monitoring of training progress.
- Advanced data post-processing capabilities.
Streamline your research and development in fuel cell modeling with this versatile toolkit!