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:
- 5d704cb5b07f8ccaad25c9636884f4e266c4f6b47d0125d3184c7bdb24a4198b
- Size of remote file:
- 1.47 GB
- SHA256:
- 81bd49719384ac79499b77071edcf7eaa0c0002b018b7bf435687f6b9ce2c091
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