Teknosys learning library

14. Build and publish a language-model workflow with the Hub

Select a supported checkpoint, load its matching tokenizer, prepare task-appropriate datasets, train locally, and save model/tokenizer artifacts. Test inference with those saved artifacts before publishing. LoRA adapters need the correct base checkpoint; an adapter is not necessarily a standalone model.

Publish to a repository you control with an appropriate license and a model card explaining training data, limitations, evaluation, and intended use. Use a private repository when artifacts or metadata should not be public. Do not upload access tokens, private datasets, or checkpoints that may disclose sensitive information.

Conversion to GGUF is a later deployment step for supported architectures, not an automatic option for every Hub model.

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