Instructions to use JunHwi/kold_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JunHwi/kold_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JunHwi/kold_binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JunHwi/kold_binary") model = AutoModelForSequenceClassification.from_pretrained("JunHwi/kold_binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eab7594ca7142c6963e22cef6eb416705ff721b3f483e4add617dc5da135eee1
- Size of remote file:
- 3.31 kB
- SHA256:
- b4e078a01a37e2a547b9d964f77a486fcd0adfd219e9292556b04a888172ddbc
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