Instructions to use google-bert/bert-base-german-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-base-german-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-base-german-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-german-cased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-german-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
Multilingual powerhouse — testing for mobile deployment
#8
by 3morixd - opened
This model covers Finnish, Italian, Japanese, Polish, Urdu — exactly the kind of multilingual capability we need for global mobile AI.
At Dispatch AI (FZE, UAE), we're building mobile AI that works for everyone. Models like this are the foundation.
We benchmark multilingual models on our 40-phone farm (Snapdragon 865) to see which maintain quality across languages when quantized to 4-bit. Results vary wildly — some lose 30% quality in non-English after quantization.
Would love to see multilingual eval at different quantization levels.
- Dispatch AI (FZE), Sharjah UAE