Instructions to use yunjinchoi/klue-bert-base-p-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yunjinchoi/klue-bert-base-p-encoder with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, BertEncoder tokenizer = AutoTokenizer.from_pretrained("yunjinchoi/klue-bert-base-p-encoder") model = BertEncoder.from_pretrained("yunjinchoi/klue-bert-base-p-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yunjinchoi/klue-bert-base-p-encoder: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/yunjinchoi/klue-bert-base-p-encoder/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://yunjinchoi/klue-bert-base-p-encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yunjinchoi/klue-bert-base-p-encoder/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 3d4ae0d2013108a0666dfc795390532198804da9fc348c43a6746e0b65ffb0d2
- Size of remote file:
- 443 MB
- SHA256:
- 30b22badcfc43a012b83d6a13c518fd82fbd1ed0bda891aa851f126125e80e12
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