Instructions to use EdBerg/outputs5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EdBerg/outputs5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("EdBerg/outputs5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 630a8c7ffbd1ea0d7a8192a1cdcdf4cab8067c5a19d2177bf904a7d8943f9ee3
- Size of remote file:
- 5.5 kB
- SHA256:
- 0a9db1df610f09ace51cfab2b676b74403d763563f8025f4e6208f14e39922b3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.