Instructions to use kamizane/FineTuningJsonscheme3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kamizane/FineTuningJsonscheme3B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kamizane/FineTuningJsonscheme3B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc76ead4e49fd7c029c91e61764d121c9afd10150342499a558453fa47034d0c
- Size of remote file:
- 14.8 kB
- SHA256:
- f34538e7a551e5723e6ba23dff8780ed04c981d85bd02f05b947d660bc63d089
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.