Instructions to use google-bert/bert-base-multilingual-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-base-multilingual-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-base-multilingual-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-multilingual-uncased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-multilingual-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 812464ff777831b8cf9a4447db847843d139febc34efdd39340bf1a53136d063
- Size of remote file:
- 672 MB
- SHA256:
- b33adb2b700b7029a64a4a14ddec6bda8555d2ca879e80a75789fd9542a6290e
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