Instructions to use c-mohanraj/gemma-lora-t with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use c-mohanraj/gemma-lora-t with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("c-mohanraj/gemma-lora-t", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 214e88bb0f027c911006c8826c9264603a807425608fc4b20aa94fcec5df2c87
- Size of remote file:
- 6.35 kB
- SHA256:
- fe5606d5cbbc60534996d39767059946e5ab0e8aad88279b84dc146125d99d96
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.