Instructions to use beva/beavers-dam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use beva/beavers-dam with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("beva/beavers-dam", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from beva/beavers-dam: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/beva/beavers-dam/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://beva/beavers-dam/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/beva/beavers-dam/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- bd94f0243712d8c21843a40082743da3b3f64e149987b361fb07d16069146c9a
- Size of remote file:
- 438 MB
- SHA256:
- 77a532dae20276d24c5396c33ef89a9dcad6c6175fc143db80d568a46bd9b9c9
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