Instructions to use BioMedTok/SentencePieceBPE-CC100-FR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BioMedTok/SentencePieceBPE-CC100-FR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BioMedTok/SentencePieceBPE-CC100-FR")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BioMedTok/SentencePieceBPE-CC100-FR") model = AutoModelForMaskedLM.from_pretrained("BioMedTok/SentencePieceBPE-CC100-FR") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbfc7667c4af3937062ddbbc8da7f05646275406aa95d6d7e512e46e1fc9d845
- Size of remote file:
- 885 MB
- SHA256:
- 5ecab411061e5ad49355148042f65f9a3954749ca2747e4632d4b94a9f03562f
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