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
TemporalMesh Transformer: 29.4 PPL at 48% compute — beats Mamba, new open-source architecture
#8 opened about 1 month ago
by
vigneshwar234
where I can get the copyright notice?
#7 opened about 1 year ago
by
joydeb
Adding ONNX file of this model
#6 opened over 2 years ago
by
Mesc70
Fix malformed tokenizer config and add special tokens map
#4 opened about 3 years ago
by
Xenova
Purpose of pytorch_model.bin
#3 opened about 3 years ago
by
123-pooja