Instructions to use beomi/kcbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beomi/kcbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="beomi/kcbert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("beomi/kcbert-base") model = AutoModelForMaskedLM.from_pretrained("beomi/kcbert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from beomi/kcbert-base: direct link, hf CLI and curl.
- Browser
- Download file 49 Bytes
-
https://huggingface.co/beomi/kcbert-base/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://beomi/kcbert-base/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/beomi/kcbert-base/resolve/main/tokenizer_config.json
49 Bytes
| {"do_lower_case": false, "model_max_length": 300} |