Instructions to use TeleEmbodied/SMART-VLA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeleEmbodied/SMART-VLA with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TeleEmbodied/SMART-VLA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/slide4-4k.png from TeleEmbodied/SMART-VLA: direct link, hf CLI and curl.
- Browser
- Download file 5.37 MB
-
https://huggingface.co/TeleEmbodied/SMART-VLA/resolve/main/assets/slide4-4k.png
- Command line
-
hf download hf://TeleEmbodied/SMART-VLA/assets/slide4-4k.png
-
curl -L -o slide4-4k.png https://huggingface.co/TeleEmbodied/SMART-VLA/resolve/main/assets/slide4-4k.png
5.37 MB

- Xet hash:
- 74b7b241b2286aabdb4bf2b66abfc89c4fffc30ccd756070e40544cf0e203dea
- Size of remote file:
- 5.37 MB
- SHA256:
- c64e99e4d80eecb9be8152b1fe6e8f6566ff4256ee8b4ba65e0f1863b1f23c48
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.