Instructions to use nateraw/custom-torch-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nateraw/custom-torch-model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nateraw/custom-torch-model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56441b8858c9ca92a4ceeb9c8648b87047052806d9da5d8c77a78399bd18a0a0
- Size of remote file:
- 1.06 kB
- SHA256:
- 9db4bc1b10f49000e14afd1a3e389c4d60e073583762283091b4e4d82166f78b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.