That's a lightweight vision-language-action model, which targets single-GPU training and edge deployment use cases. The original implementations can be found here. The model takes images from one or multiple cameras, robot state, and language instruction and produces a chunk of actions, which robot can execute as a sequence of movements in real world.

The model weights are converted from the official HF repo and can be directly applied in the LIBERO virtual benchmark environment.

To fine-tune your model with a custom dataset, you can use Physical AI Studio.

The following API example showcases inference API for this model:

The following API example demonstrates how to run the model on LIBERO:

Note that the model should be downloaded and saved to the smolvla-libero-fp16-ov folder prior to running this script.

The original model is distributed under Apache 2.0 license.

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