Instructions to use google-bert/bert-base-multilingual-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-base-multilingual-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-base-multilingual-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-multilingual-cased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-multilingual-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcbe6d46b2899c8f0970267ca42e7114e4742c6a635419b329b83ad6fb05a254
- Size of remote file:
- 712 MB
- SHA256:
- ebee9a143c50f975a7d5074642150011e112a65d8362dd6b6b84867ee689f2ad
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