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:
- e2fc23f383564bfa81114aefeb22d098cce323d288a42c9749085ea0b4f50d51
- Size of remote file:
- 999 MB
- SHA256:
- 77d2ed6e37792d0e3224dddf5d4b509c65d0e9fb131b97339598b852ccd83921
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