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 pytorch_model.bin 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/pytorch_model.bin
- Command line
-
hf download hf://beva/heb-beavers-dam/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/beva/heb-beavers-dam/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- d05011b6b391a7f1aea6e528262ed69b7e79746915b62227cc9a18c876c073b5
- Size of remote file:
- 438 MB
- SHA256:
- 1f2a4951ed42a5c1eda6c20608db3029124da2b7ef5b3db4880eb1d76645aab2
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