Instructions to use lIlBrother/ko-answerable with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lIlBrother/ko-answerable with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lIlBrother/ko-answerable")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lIlBrother/ko-answerable") model = AutoModelForSequenceClassification.from_pretrained("lIlBrother/ko-answerable") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e602d172fbe1e2150da7953ed8f61bb769dfae78e534062f518682cb43df820
- Size of remote file:
- 457 MB
- SHA256:
- d6d0e8c491d76d948cc56b8a8b5b76a6e01f4a28951fde29001066d70afb4b37
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