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.
Project details
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