Deploy and Test Your Model
Download your trained VLM and run inference on new images using the Vi SDK.
A completed training run, Python 3.10+ installed locally, your secret key and organization ID, and a few test images not in your training dataset.
When your training run finishes, the model weights stay in Datature Vi until you download them. Vi SDK means the Datature Vi Python package: it pulls those weights to your machine and runs predictions on image files. NVIDIA NIM is an optional path for teams that want the same model packaged as an NVIDIA inference container instead of a raw Python script.
This guide covers finding your run ID, then downloading and running inference. For NIM-based serving, see the NIM deployment guide. For full API details, see the Vi SDK reference. To rename, edit keys, or delete downloads, see manage models.
Install the Vi SDK with inference support
Open a terminal and run the above command to install the SDK with PyTorch, Transformers, and other inference libraries. Replace [inference] with [all] to install all optional features. See the Vi SDK installation guide for GPU setup and environment options.
What to do if predictions look wrong
If your model's predictions do not match your expectations, check these things in order:
Your deployment is working when the SDK returns predictions without errors for your test images and the output reflects your training task.
Next steps
Updated 4 months ago