Instructions to use rail-berkeley/octo-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rail-berkeley/octo-small with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rail-berkeley/octo-small", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b7b542f07ab90abd3486dea94c8c4567468458363f4a5f48432c662bdc94702
- Size of remote file:
- 738 kB
- SHA256:
- 0ce74dd8e433ce4a8a1534c4ab9687d9fc3e444b3eece750047dcb22125d73ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.