Instructions to use tkcho/commerce-bert-kr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tkcho/commerce-bert-kr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tkcho/commerce-bert-kr")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tkcho/commerce-bert-kr") model = AutoModelForMaskedLM.from_pretrained("tkcho/commerce-bert-kr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8226f7bf5496e4f5819420ec4a5c7cad3db4e700661784bb2e44a78edcedeb9
- Size of remote file:
- 473 MB
- SHA256:
- bc474c6de9b88fb15d81c0443f1ea5b814fac8a06e672d07185167e0cfe114dd
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