Instructions to use google-bert/bert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-cased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 425b92f055cc09f956915f0fe623aa873ef0c7978d30c7f2b46cd21e491cfbdd
- Size of remote file:
- 527 MB
- SHA256:
- 0d04ece69d04b890153ea3bd5c2ef5706f9181495a0778a2593c6118f7ce2dc3
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