monad.run

Trains the foundation model in one of two ways:

• Run both training stages in a joint pipeline using the --pretrain argument.

  Shell

  python -m monad.run 
  --pretrain 
  --config-path "path/to/config.yml" 
  --features-path "path/to/store/pretrain/artifacts" 
  --overwrite

• Run training in separate stages, which may be helpful—for example—in a dual-environment setup. In this case, you will execute run two times with arguments: --fit and --fm.

  Shell

  python -m monad.run \
  --fit \
  --config-path "path/to/config.yml" \
  --features-path "path/to/store/pretrain/artifacts" \
  --overwrite
  
  python -m monad.run \
  --fm \
  --features-path "path/to/store/pretrain/artifacts" \
  --overwrite

--pretrain: First validates the configuration, then automatically runs both training stages: it fits the behavioral representation, and finally trains the foundation model using the output from the fitting step.

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--fit: Fit behavioral representation. This stage analyzes the data and builds the feature representation needed for model training.

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--fm: Train foundation model based on fitted behavioral representation. Please note that config-path should no longer be provided; BaseModel will use the configuration file stored at the fitting stage.

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The table below summarizes the availability of command-line parameters across different execution contexts. Each argument is exclusive to the command(s) listed in its row .