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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download neuron/model.neuron from google-bert/bert-base-multilingual-cased: direct link, hf CLI and curl.
- Browser
- Download file 1.01 GB
-
https://huggingface.co/google-bert/bert-base-multilingual-cased/resolve/refs%2Fpr%2F14/neuron/model.neuron
- Command line
-
hf download hf://google-bert/bert-base-multilingual-cased@refs/pr/14/neuron/model.neuron
-
curl -L -o model.neuron https://huggingface.co/google-bert/bert-base-multilingual-cased/resolve/refs%2Fpr%2F14/neuron/model.neuron
1.01 GB
- Xet hash:
- 3f01c0bcb21ad3d99dd91e91147f59833866e8e67a420ce21dc43b7c0c4a332d
- Size of remote file:
- 1.01 GB
- SHA256:
- adcac2953797de08be1688b29c1236111b2a10e27243025e67ea11a0b8f8a203
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