Instructions to use BioMedTok/BPE-HF-CC100-FR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BioMedTok/BPE-HF-CC100-FR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BioMedTok/BPE-HF-CC100-FR")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BioMedTok/BPE-HF-CC100-FR") model = AutoModelForMaskedLM.from_pretrained("BioMedTok/BPE-HF-CC100-FR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 520dde1eb0e6790af7914db0cdc1ca0bd9bbde9cdf698eaac6fb3c54022f52f5
- Size of remote file:
- 3.5 kB
- SHA256:
- b27b431b0fa86abf313f510872bea9b8c29fe47ce594c2b8efeda5e3e9857366
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