Instructions to use ltg/bnc-bert-span-order with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltg/bnc-bert-span-order with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ltg/bnc-bert-span-order")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("ltg/bnc-bert-span-order", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c9aadb38b820f36b1d063b61e2c6b03882636b5335d8a1546481601d2f4c7e4
- Size of remote file:
- 418 MB
- SHA256:
- 6d89054282b6d266e0506f60d2cb75c7fbc44a6eb66b47ec4e20113571b39c7e
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