Instructions to use google-bert/bert-large-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-large-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-large-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-large-cased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-large-cased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df442ee2964308ed6114ffc7d94588b5df9fe409e72c1528d08baa2099b9b9a2
- Size of remote file:
- 1.24 GB
- SHA256:
- d8c8e92f883363b97ae60161831c6cfe64b0004d7a08731e344feb902618ae8b
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