Instructions to use klue/bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use klue/bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="klue/bert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("klue/bert-base") model = AutoModelForMaskedLM.from_pretrained("klue/bert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from klue/bert-base: direct link, hf CLI and curl.
- Browser
- Download file 445 MB
-
https://huggingface.co/klue/bert-base/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://klue/bert-base@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/klue/bert-base/resolve/refs%2Fpr%2F1/pytorch_model.bin
445 MB
- Xet hash:
- fcd90a0b1a7b30fb1c26a5b541dff5b732fd33f0cdae2ccfc74efaaabdf1e1d3
- Size of remote file:
- 445 MB
- SHA256:
- 757d1c1fcfe3b4f01445bf62d5e654b99ea08f5ea1aca7d180ed91c004668c6d
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