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:
- 74caf0e913848a3a692699b0ff37742798a24c1f7d9c8421108f1c5368bd26dd
- Size of remote file:
- 532 MB
- SHA256:
- 44d7a2896d341c51fb1eba89aea3a590e6af0ce33e25481136f7eeecb62e5f7f
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