The August sale-exploration report has been overtaken by Nvidia’s September 3 acquisition agreement. The useful engineering question it raised remains: can your application start with the intended model when the Hub is unreachable?
The news has moved on
Nvidia’s official announcement confirms an agreement for about $12.93 billion. Our updated acquisition report covers the platform commitments. This page keeps the earlier story’s practical thread: dependence on live downloads during startup.
An ownership announcement does not itself prove an impending outage. Offline preparation is useful because network access, repository availability and local application startup are separate dependencies under any owner.
Pin the input before warming the cache
Hugging Face’s download guide documents the revision parameter, including a full commit hash, for version-specific retrieval. A branch name such as main can resolve to different files on different days. Record the resolved revision rather than just the repository name.
Build an artifact inventory from what the application actually loads: weight shards and their index, tokenizer files, model configuration and any required local code. A download restricted to JSON files might populate configuration successfully while leaving all weights absent. “Download succeeded” only describes the requested files.
A three-state rehearsal
Use a disposable test environment with a dedicated cache and the intended runtime. First, populate the required revision with network access. Second, start the application using that populated cache with Hub access disabled. Third, repeat with an empty test cache and confirm that missing data produces an explicit failure. The third state verifies that the successful state was not silently downloading files from somewhere else.
The documented HF_HUB_OFFLINE setting suppresses Hub HTTP requests in huggingface_hub and causes unavailable cached downloads to fail. Set it before starting the process. It is not a system firewall: other application libraries or remote inference calls can still use the network. A rehearsal of complete offline operation needs network controls covering the whole test process.
Define success beyond finding files
For an original acceptance worksheet, record four outcomes: the resolved revision, all required files present, successful model loading, and a completed fixed inference input with the expected output structure. File hashes help verify identity, but they do not demonstrate that the runtime can execute the model.
Keep cached artifacts within their applicable access and license permissions. A hosted inference API cannot be made local merely by caching its client package. This is a proposed dependency rehearsal, not a claim that PeopleAreGeek downloaded or ran every model on the Hub.
Update sale exploration with confirmed September 3 agreement; retain a distinct useful offline-dependency audit instead of duplicating the later acquisition report.