Instructions to use SharedBailii/PT-CaseLawBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SharedBailii/PT-CaseLawBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SharedBailii/PT-CaseLawBert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SharedBailii/PT-CaseLawBert") model = AutoModelForMaskedLM.from_pretrained("SharedBailii/PT-CaseLawBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SharedBailii/PT-CaseLawBert: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/SharedBailii/PT-CaseLawBert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SharedBailii/PT-CaseLawBert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SharedBailii/PT-CaseLawBert/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- a19c5286dc697aa5183f23b79dd0a0fb64bcd299e59a428848dab0606aaf3456
- Size of remote file:
- 438 MB
- SHA256:
- 6c38f41cb3c266a33c73a027bed965971657ef4cc0d7362557aecb5640fe0489
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