KerasHub is a production-grade Keras 3 library providing pretrained model architectures, layers, tokenizers, metrics, and sampling utilities for NLP, vision, multimodal, and audio tasks. The codebase is organized around a consistent Backbone → Task → Preprocessor pattern, where each model family (e.g., BERT, Gemma, ViT, Whisper) defines a backbone, a preprocessor (tokenizer + optional media converter), and task-specific heads (CausalLM, ImageClassifier, etc.). All models expose a unified `from_preset()` API for loading pretrained weights hosted on Kaggle Models, and `save_to_preset()` for export. The library includes extensive checkpoint conversion tooling from HuggingFace and TIMM, export to HuggingFace format and OpenVINO, and integration with vLLM for serving. While predominantly an application library, it has strong data/research character through its pretrained weight infrastructure, benchmark scripts, and research-oriented architectures (e.g., FNet, RWKV7, BLIP-2).