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:
- d746390c0ab9e62475e4578d980dedddbc424f6ec09bb1b2517389fb3b25e3dd
- Size of remote file:
- 11.4 MB
- SHA256:
- a44bdeb203b51e0bc7615c0e920f5278ebdac0a51146a9177a3d428030305168
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.