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:
- f0cf14d226c86f822878335b562070c7261144f1f9c1b7e0b576c217b4dffc77
- Size of remote file:
- 500 MB
- SHA256:
- 1169479fbf819cbca67bb8fbef0922b31789415f0580a4c19ea192da62b69d63
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.