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%2F13/neuron/model.neuron
- Command line
-
hf download hf://google-bert/bert-base-multilingual-cased@refs/pr/13/neuron/model.neuron
-
curl -L -o model.neuron https://huggingface.co/google-bert/bert-base-multilingual-cased/resolve/refs%2Fpr%2F13/neuron/model.neuron
1.01 GB
- Xet hash:
- 6912d0c82b3449461d95bd7284e4a11bf3bcb191df4ce582d23c44d9141b3c65
- Size of remote file:
- 1.01 GB
- SHA256:
- 06aa12948af5872eef1b43e7fec8269a551c9273a9854af53a62b2b14bf8be07
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