Instructions to use law-ai/CustomInLawBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use law-ai/CustomInLawBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="law-ai/CustomInLawBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("law-ai/CustomInLawBERT") model = AutoModelForMaskedLM.from_pretrained("law-ai/CustomInLawBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9481ccaa26f5bb48fcfd8e6e378dccfc08a3097f2ae4ba48a16d275647a0f2f8
- Size of remote file:
- 534 MB
- SHA256:
- 525d803f7d244f22e0010b7fab3f8090afcda85ee4b68ff4e45c6d3d19cbfea0
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