Instructions to use lgrobol/BERTrade-camemBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgrobol/BERTrade-camemBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lgrobol/BERTrade-camemBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lgrobol/BERTrade-camemBERT") model = AutoModelForMaskedLM.from_pretrained("lgrobol/BERTrade-camemBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bb410da16cdf1dcbbd526cdae56b903b3417a66ac4b4d675d4dc369b97ef29b
- Size of remote file:
- 443 MB
- SHA256:
- d87577951cf13a139f9ca768213e2f21a1917780e21788775e872a3b9d2355b8
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