Skip to main content
When training completes, you get a registered model artifact that’s ready to deploy. No manual promotion step — it goes straight from “done” to “deployable.”

​
What you see

  • Final eval results — the trained model’s scores on your eval dataset, compared against the baseline from before training started
  • Model artifact — registered in the platform and visible on the Models page
  • Deploy button — appears on the training details page and on your model’s row in the Models page
Completed training run with final eval results and Deploy button

​
Is it actually better?

Compare the trained model’s final eval scores against the off-the-shelf models you benchmarked earlier in Eval. If the trained model scores higher on your rubric, it’s ready to deploy. If not, you may need to iterate on your training data or recipe.

​
Next steps

Deploy your model

Ship it to a dedicated GPU.

Troubleshooting

If training failed or results aren’t what you expected.