NeuralForecast offers a comprehensive set of neural forecasting models ranging from classic RNNs to modern Transformers including NBEATS, NHiTS, DeepAR, and temporal fusion transformers. Built on PyTorch, it provides scalable and user-friendly implementations for training and inference with probabilistic forecasting capabilities. The library focuses on performance and robustness for univariate and hierarchical time series prediction tasks.