Instructions to use beomi/kcbert-base-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beomi/kcbert-base-dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="beomi/kcbert-base-dev")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("beomi/kcbert-base-dev") model = AutoModelForMaskedLM.from_pretrained("beomi/kcbert-base-dev") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef8b5b8ff0c03b6e4ce6c0cc2ebc120852137d8fe60ee8edbd0439741e6fb660
- Size of remote file:
- 438 MB
- SHA256:
- 0983c6740f7c612edf1ed0d219bc66f79e33b86856cf6b7bf4369654552722e0
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