Instructions to use HCKLab/BiBert-NSP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HCKLab/BiBert-NSP with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("HCKLab/BiBert-NSP") model = AutoModel.from_pretrained("HCKLab/BiBert-NSP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from HCKLab/BiBert-NSP: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/HCKLab/BiBert-NSP/resolve/main/training_args.bin
- Command line
-
hf download hf://HCKLab/BiBert-NSP/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/HCKLab/BiBert-NSP/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 78a1d0ed400eda4138d8b9c0baa1e249fde0258587689f39874c0315547c0787
- Size of remote file:
- 4.09 kB
- SHA256:
- a976d98f6dbbeb852cf010f89912eedc76d21c6f1e6ec1398e0673a8edd547ae
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