Instructions to use Geotrend/bert-base-10lang-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Geotrend/bert-base-10lang-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Geotrend/bert-base-10lang-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-10lang-cased") model = AutoModelForMaskedLM.from_pretrained("Geotrend/bert-base-10lang-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 362efaf074fa166e64a2f130aba95f06f057d6f0f8202e65dbd2b6b0b86b9b2a
- Size of remote file:
- 551 MB
- SHA256:
- f13183cec2e8467dfcaa10181954923192d238a42c60f4b4e1b1948288351186
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.