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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from google-bert/bert-base-multilingual-uncased: direct link, hf CLI and curl.
- Browser
- Download file 1.72 MB
-
https://huggingface.co/google-bert/bert-base-multilingual-uncased/resolve/refs%2Fpr%2F4/tokenizer.json
- Command line
-
hf download hf://google-bert/bert-base-multilingual-uncased@refs/pr/4/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/google-bert/bert-base-multilingual-uncased/resolve/refs%2Fpr%2F4/tokenizer.json
1.72 MB
File too large to display, you can check the raw version instead.