trunk/e533c0115b8734326de72ab483e68977c59c8b6f: Update assigntome-docathon.yml for 2026 Docathon (#181264)

PyTorch, the popular open-source deep learning framework maintained by Meta, has merged a small but significant pull request (PR #181264) updating its GitHub workflow for the upcoming 2026 Docathon. The change, authored by sekyondaMeta and approved by albanD, modifies the assigntome-docathon.yml file by updating a label used in the automatic assignment workflow. This ensures that contributors can correctly self-assign issues during the 2026 edition of the Docathon, a recurring community event focused on improving PyTorch's documentation.

While this commit is minor in scope—essentially a label update—it highlights the ongoing maintenance and preparation for large-scale community contributions. The Docathon is a key event where PyTorch developers and users collaborate to enhance documentation, fix errors, and write guides. By updating the workflow well in advance, the PyTorch team ensures a frictionless experience for participants, allowing them to focus on quality improvements rather than administrative hiccups. This attention to detail reflects the project's commitment to its massive community of 99.6k stars and 27.6k forks.