Instructions to use muralcode/Oracle.Aritha.AM-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muralcode/Oracle.Aritha.AM-1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("muralcode/Oracle.Aritha.AM-1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bb0b8d126cdc819225c4f8174addebc0be59b127459434cf5823f91458db7dd
- Size of remote file:
- 6.23 kB
- SHA256:
- b96fb792ca0ab56852b7731173df06e5de7edac4f973104e9963d9b0b1160cfc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.