Instructions to use google-bert/bert-large-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-large-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-large-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-large-uncased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-large-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 885bf30283ace3f8f3b076c6efdcab4254c2da4303ea1707fd4108fee0bc6b3d
- Size of remote file:
- 1.47 GB
- SHA256:
- 9db92b28d6fb0e5ab770b24ed27bde941d1f314a3c5e8c28d698025cc1807d7f
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