Instructions to use Jakobbbjorner/fen-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jakobbbjorner/fen-full with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Jakobbbjorner/fen-full", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47f88c16dc1b279edef7550d17fa1089b88c3bec018ec466aced15a12a98259a
- Size of remote file:
- 11.4 MB
- SHA256:
- 88a3a6fcb80132f76da8aa40cdc3fccd7e5d8468ef15421f5b0c2715e85217d2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.