Instructions to use ekiprop/KantaiBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ekiprop/KantaiBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ekiprop/KantaiBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ekiprop/KantaiBERT") model = AutoModelForMaskedLM.from_pretrained("ekiprop/KantaiBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a96e370cab8da8b9ab35c68e528f17ece940d9af3ffa081aec2efce1600ac27c
- Size of remote file:
- 5.65 kB
- SHA256:
- 725ab4f9d20452a2ceddc9044660c07f66da7ad8db1739c7590678cc09e6a7a9
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