Instructions to use beva/heb-beavers-dam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beva/heb-beavers-dam with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("beva/heb-beavers-dam", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_weights.pt from beva/heb-beavers-dam: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/beva/heb-beavers-dam/resolve/main/model_weights.pt
- Command line
-
hf download hf://beva/heb-beavers-dam/model_weights.pt
-
curl -L -o model_weights.pt https://huggingface.co/beva/heb-beavers-dam/resolve/main/model_weights.pt
438 MB
- Xet hash:
- b76abb8ca45a065eb21eae4b94fcd3e22431696dc131dc2b97e7b92fce97f4e9
- Size of remote file:
- 438 MB
- SHA256:
- 6042e788aad607a352bc91c64deac9de05e5feedda92707140c3fed80612477b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.