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")# 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") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding Neuron-optimized model files
#14 opened 12 months ago
by
badaoui
Adding Neuron-optimized model files
#13 opened 12 months ago
by
badaoui
Request: DOI
#12 opened over 1 year ago
by
Marcos08523
Using bert-multilingual as a cross-lingual re-ranker
#10 opened about 2 years ago
by
victorkeke
Adding `safetensors` variant of this model
#9 opened about 2 years ago
by
Creationsv2
Adding ONNX file of this model
#8 opened about 2 years ago
by
Mesc70
[AUTOMATED] Model Memory Requirements
#7 opened about 2 years ago
by
model-sizer-bot
[AUTOMATED] Model Memory Requirements
#6 opened about 2 years ago
by
model-sizer-bot
Fix malformed tokenizer config and add special tokens map
#4 opened about 3 years ago
by
Xenova
How to start fine-tuning the model using bert-base-multilingual-cased
#2 opened over 3 years ago
by
DivyaK