Instructions to use colinglab/BureauBERTo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use colinglab/BureauBERTo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="colinglab/BureauBERTo")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("colinglab/BureauBERTo") model = AutoModelForMaskedLM.from_pretrained("colinglab/BureauBERTo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84c2b28f5ad2284bfec9760a69bbaaefbd5c1a69f51a1aaee5f56eef832b294a
- Size of remote file:
- 468 MB
- SHA256:
- 9470a3939f658e6905ac53a0eff9019852b27e58c90cce1356871844a53decc7
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