WeSpeaker provides tools for speaker embedding learning with applications to verification, recognition, and diarization tasks. It implements various neural network architectures including ECAPA-TDNN, CAMPLus, ResNet, and utilizes self-supervised learning models like WavLM and DINO for feature extraction. The toolkit supports both online feature extraction and loading pre-extracted features, and provides pretrained models for Chinese and English speaker tasks.