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CLI for the PriorStudio framework — scaffold, validate, lint, and run prior-fitted foundation model projects.

Project description

priorstudio — CLI

The command-line interface for PriorStudio, the toolkit for training prior-fitted foundation models.

Install

pip install priorstudio

For training (requires PyTorch):

pip install "priorstudio[torch]"

Commands

priorstudio init <dir>            # scaffold a new FM project
priorstudio validate <path>       # check artifacts against JSON Schema
priorstudio lint <project>        # cross-reference + style checks
priorstudio sample <prior.yaml>   # draw N tasks from a prior
priorstudio run <run.yaml>        # execute a training run end-to-end
priorstudio predict <run-dir>     # inference against a trained checkpoint
priorstudio export <project>     # tar-gzipped project archive

Run priorstudio --help for the full list and <cmd> --help for each subcommand's flags.

What this CLI is for

PriorStudio organises every PFN project around five first-class artifacts: priors (synthetic data generators), models (block compositions), evals (benchmarks + metrics), runs (training manifests), and initiatives (research workstreams). This CLI operates on the file layout those artifacts produce — scaffolding new projects, validating them, running training, and exporting them for sharing.

The full story (concepts, architecture, examples, marketplace catalog) lives at the main repo: github.com/profitopsai/priorstudio

License

Apache-2.0.

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