Instructions to use bertin-project/bertin-base-stepwise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertin-project/bertin-base-stepwise with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bertin-project/bertin-base-stepwise")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-base-stepwise") model = AutoModelForMaskedLM.from_pretrained("bertin-project/bertin-base-stepwise") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e7a21397f103dda05b05a09e7b093a1424a22632ffdb6384f96bd0526f27a50
- Size of remote file:
- 250 MB
- SHA256:
- 874aacbf3c75f4c0b6bcf868d8dcf249ea5cbc6b3c3d551b3d329accac9b2fc8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.