Instructions to use lentohaihane/r-4b-sft-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lentohaihane/r-4b-sft-code with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lentohaihane/r-4b-sft-code", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af568d34f0f9a8bb384c37b2864440035060c4063bcd439a0522703d33dc4afc
- Size of remote file:
- 6.23 kB
- SHA256:
- ed7b78860f1002864e13a436624a3dfc16f82160dbace38a0e3221aebb34954a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.