Hugging Face Hub

Load LibreYOLO checkpoints from Hub repositories and publish trained checkpoints.

Install

bash

pip install "libreyolo[hf]"

Load

Python

from libreyolo import LibreYOLO, SAMPLE_IMAGE model = LibreYOLO("hf://LibreYOLO/LibreYOLO9s/LibreYOLO9s.pt", device="cpu")print(model(SAMPLE_IMAGE).boxes)

The accepted forms are owner/repo, hf://owner/repo and hf://owner/repo@revision/filename. A local path wins over a bare repository ID. Explicit hf:// bypasses that precedence. Revisions must be slash-free branch names or commit hashes.

Without a filename, a repository must have one checkpoint. An ambiguous repository raises and lists the choices. Hub checkpoints require LibreYOLO metadata or a recognized upstream conversion. Downloads use the shared Hub cache.

Publish

model.push_to_hub(repo_id, private=False, license=..., metrics=...) creates the repository if needed and uploads model.pt with a generated card. Authenticate with hf auth login or HF_TOKEN; publishing requires write access.

Training logger

Pass loggers="hf:owner/repo" or a HuggingFaceHubLogger instance. The logger checks write access and creates a missing target repository at construction. It uploads the best checkpoint at train end, falling back to the last checkpoint. The logger defaults to a private repository; explicit push_to_hub() defaults to public. Existing repositories keep their visibility.