Hugging Face: Hub, routed/hosted inference, and transformers

Hugging Face is three surfaces, and you should always know which one you are on:

1. The Hub — versioned git repos for models, datasets, and Spaces. You search it, you hf download / hf upload, you read and write model cards.
2. Inference — three ways to actually run a model: the Inference Providers router (serverless, you own nothing), a dedicated Inference Endpoint (you own a deployment that autoscales), or local transformers (you own the machine).
3. The catalog — 1M+ open models you choose from by task, license, and size.

The whole skill is choosing the right surface for the job and proving it works: a 200 router response, a live endpoint URL, a pushed repo commit. If the model is open and the workflow lives on huggingface.co, you are in the right place. Operating the GPU box yourself is ../ollama/SKILL.md (your machine) or ../runpod/SKILL.md (a rented box); training weights is ../finetuning/SKILL.md.

Decision: how should I run this model?