Instructions to use moojink/openvla-7b-oft-finetuned-libero-goal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moojink/openvla-7b-oft-finetuned-libero-goal with Transformers:
# Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("moojink/openvla-7b-oft-finetuned-libero-goal", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee242a47f30b04fb9caafa80c8cee11510b32be82113bf9e5f9ad98dc9470b51
- Size of remote file:
- 813 Bytes
- SHA256:
- 7577940217bcf5275d6049ab1230176715655baf90024b37e82b4d918e8d3216
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.