Instructions to use OWG/bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OWG/bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="OWG/bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("OWG/bert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("OWG/bert-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab6c49c85b59fb8aff20b54d2784655012e7d09a45e9c429e07789c36b211d63
- Size of remote file:
- 438 MB
- SHA256:
- 0b78761aca53753555343ae4379ffeb9f21aed4f5280ea1c149ae6331ed07360
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.