Instructions to use yuneun92/koCSN_SAPR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yuneun92/koCSN_SAPR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yuneun92/koCSN_SAPR")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yuneun92/koCSN_SAPR", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98d1ef06102138bb9474904579baf29a1b4b96a95722719a772c69eaa2aa92f2
- Size of remote file:
- 2.13 GB
- SHA256:
- 005d977ce1a796146ff3eead5e9db6c79cb5bc714245c110fd4c11b7b587254f
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