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:
- 3f8a2b2e985efcc7edd150dfe0a195583cdb27f469830f8a307fb57d2642dfa2
- Size of remote file:
- 250 MB
- SHA256:
- b8ef77804b5f055189a0eb4b259cc359ec0cb6cd04426fb3d99891dce6f7d371
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.