Instructions to use beomi/kcbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beomi/kcbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="beomi/kcbert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("beomi/kcbert-base") model = AutoModelForMaskedLM.from_pretrained("beomi/kcbert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d54f8ebaec71e64257e550bf0926be0707de69d6ae6a96dd9f79cbcb795f6339
- Size of remote file:
- 438 MB
- SHA256:
- e769d982d28549c23a22ae6cd1d4bb4e0df01d507d99ce64a4f18a57684634fa
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