Instructions to use AiresPucrs/bert-base-bookcorpus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AiresPucrs/bert-base-bookcorpus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AiresPucrs/bert-base-bookcorpus")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AiresPucrs/bert-base-bookcorpus") model = AutoModelForMaskedLM.from_pretrained("AiresPucrs/bert-base-bookcorpus") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6792c3c11a536a2c201b1c6fcf0bb9653954b7e3b59ae8deaec978f274606b1
- Size of remote file:
- 438 MB
- SHA256:
- 91684572e87a92252e3bfa75ce33e37efa796b41fdd699b737c7d9734687fa31
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