Instructions to use chaimag/ko_bert_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chaimag/ko_bert_trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="chaimag/ko_bert_trained")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("chaimag/ko_bert_trained") model = AutoModel.from_pretrained("chaimag/ko_bert_trained") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3e1a3d91f6325e16e34df263185a91f0f25084f4c2ae64a5918dc1b300735fde
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size 473211752
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