Running Locally

Step 1 — Generate a config

theseus configure gpt/pretrain run.yaml

That writes a fully-populated run.yaml with all default values filled in. Open it up and you'll see every knob the job exposes.

You can also override values inline:

theseus configure gpt/pretrain run.yaml training.per_device_batch_size=8 \
    model.n_layers=12

Planning to run on a specific chip? Bake the hardware request into the config now so you don't have to repeat it later:

theseus configure gpt/pretrain run.yaml --chip h100 -n 4

Step 2 — Run it

theseus run my-gpt-run run.yaml ./output

• my-gpt-run is a human-readable name for this run (used for logging/checkpointing).
• ./output is where checkpoints, logs, and results land.

Override config values at run time the same way:

theseus run my-gpt-run run.yaml ./output \
    training.per_device_batch_size=4

If you want to attach the run to a W&B project or group:

theseus run my-gpt-run run.yaml ./output \
    --project my-project --group ablation-lr