Instructions to use OpenMOSS-Team/RoboOmni-LIBERO-Spatial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMOSS-Team/RoboOmni-LIBERO-Spatial with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("OpenMOSS-Team/RoboOmni-LIBERO-Spatial") model = AutoModelForMultimodalLM.from_pretrained("OpenMOSS-Team/RoboOmni-LIBERO-Spatial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from OpenMOSS-Team/RoboOmni-LIBERO-Spatial: direct link, hf CLI and curl.
- Browser
- Download file 11.8 MB
-
https://huggingface.co/OpenMOSS-Team/RoboOmni-LIBERO-Spatial/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://OpenMOSS-Team/RoboOmni-LIBERO-Spatial@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/OpenMOSS-Team/RoboOmni-LIBERO-Spatial/resolve/refs%2Fpr%2F1/tokenizer.json
11.8 MB
- Xet hash:
- bd7ba53437ee9e3317f1fc3fdb7f8b353daf41fd555afae3ebbc4f13d4fded58
- Size of remote file:
- 11.8 MB
- SHA256:
- 59a0b2549430d5f560b76cb21b5fb441a8bdf163b6b27091f66e8c1476498870
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.