#Meta-learning

This project provides a PyTorch implementation of OpenAI's Reptile algorithm, focusing on meta-learning with the Omniglot dataset. While MiniImagenet support is pending, key features include TensorboardX monitoring, resumable training sessions, and K-shot N-way task sampling. Users can structure Omniglot data and modify hyperparameters for optimized learning. Contributions and feedback are welcome for ongoing improvements.

LibFewShot provides broad support for various few-shot learning techniques, including non-episodic, meta-learning, and metric-based methods. It offers users a streamlined installation process, detailed documentation, and verified configuration for reliable results. Access renowned datasets such as Stanford Dogs and miniImageNet for research purposes. Designed for academic researchers, LibFewShot fosters community contributions and operates under the MIT License.