A primary deep learning framework for research and production. Its eager execution and autograd make experimentation fast, while the ecosystem supports vision, NLP, audio, and distributed training. We rely on PyTorch for training and fine‑tuning neural networks, building LLM/agent components, and optimizing inference for deployment. It integrates smoothly with modern tooling (model hubs, accelerators, and MLOps stacks) for reliable end‑to‑end delivery.