Instructions to use maastrichtlawtech/legal-distilcamembert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maastrichtlawtech/legal-distilcamembert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="maastrichtlawtech/legal-distilcamembert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("maastrichtlawtech/legal-distilcamembert") model = AutoModelForMaskedLM.from_pretrained("maastrichtlawtech/legal-distilcamembert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd63fcdb5eebb1433a0e15882493f840e00a67e9827f31f7d16334bcffc899fc
- Size of remote file:
- 273 MB
- SHA256:
- 65892a43fbfc6f8c6e3dc54db45f58e6b668330f54497855eeff59fad05336db
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