Instructions to use Kyoungmin/kcbert-base-petition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kyoungmin/kcbert-base-petition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Kyoungmin/kcbert-base-petition")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Kyoungmin/kcbert-base-petition") model = AutoModelForMaskedLM.from_pretrained("Kyoungmin/kcbert-base-petition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Kyoungmin/kcbert-base-petition: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/Kyoungmin/kcbert-base-petition/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Kyoungmin/kcbert-base-petition/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Kyoungmin/kcbert-base-petition/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- 64558ae912821a85157a97a80bd577fd38f07ebbd461699ec6ae7ca6e966b9cc
- Size of remote file:
- 436 MB
- SHA256:
- 4375dc51ce3eaa20d67c03b13d554e4b5a16a95d2e70f20b70795156912bc157
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