Instructions to use dsksd/bert-ko-small-minimal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsksd/bert-ko-small-minimal with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, BertForPretraining tokenizer = AutoTokenizer.from_pretrained("dsksd/bert-ko-small-minimal") model = BertForPretraining.from_pretrained("dsksd/bert-ko-small-minimal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dsksd/bert-ko-small-minimal: direct link, hf CLI and curl.
- Browser
- Download file 284 MB
-
https://huggingface.co/dsksd/bert-ko-small-minimal/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dsksd/bert-ko-small-minimal/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dsksd/bert-ko-small-minimal/resolve/main/pytorch_model.bin
284 MB
- Xet hash:
- afdd99031f0bec0f21d80a131010ac3c7a0731e91ac21b5d961957d8827e3502
- Size of remote file:
- 284 MB
- SHA256:
- 529500c36c4ce5a1f90715589f46702c350b334b8ce3cd74e7ae4e9b103e804b
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