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:
- 46b50482febf8c5819892bbacbce33a6f7e719049958df61c30eb9bafafe60a1
- Size of remote file:
- 1.34 GB
- SHA256:
- 95d8c4223c803edaae6af2a45ef01e28c715613550ce64f82e182692807e2b64
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