Instructions to use lgrobol/BERTrade-FlauBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgrobol/BERTrade-FlauBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lgrobol/BERTrade-FlauBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lgrobol/BERTrade-FlauBERT") model = AutoModelForMaskedLM.from_pretrained("lgrobol/BERTrade-FlauBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d63c1817a7a49f5061c3f703e870704bc9fd77e0270d43738ab35e840193add7
- Size of remote file:
- 553 MB
- SHA256:
- 0ecb94eca6171e704cdd213474dcc2ab48e31be9559d297335e65c71d2e32797
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