Instructions to use google-bert/bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d8408d3a894d02517d04956e2f7546ff08362594072f3527ce144b5212a3296
- Size of remote file:
- 440 MB
- SHA256:
- 097417381d6c7230bd9e3557456d726de6e83245ec8b24f529f60198a67b203a
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