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:
- fcc9cda23c7fd56c1256b7e02c65bd9db36cad10e19208b5aac909ae9a2376a4
- Size of remote file:
- 499 MB
- SHA256:
- ad64f4a4a6dc59c076f74458305070c918bdd03ab5bc8a3024e8b12a03aadbe5
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