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:
- 0840b157499131cf5a1ca5a053b8a2307fa8832a90b205784186f6d5b313ad65
- Size of remote file:
- 3.45 kB
- SHA256:
- e7470445bddc5587773b228efa33eb54e13828db7ea2dabe650980effe221d1e
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