Instructions to use kykim/bert-kor-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kykim/bert-kor-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kykim/bert-kor-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kykim/bert-kor-base") model = AutoModelForMaskedLM.from_pretrained("kykim/bert-kor-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2759dc67b9b82be2483725b6b65d3782a2f6fe4c0c1481f7022de83fe8b5f991
- Size of remote file:
- 473 MB
- SHA256:
- b3bfa28517a8fcf93b453595f74679302a90a04b1d114cc7133971690b2be93e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.