Instructions to use karths/binary_classification_train_usab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_usab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_usab")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_usab") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_usab") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c2e310170ac472a1673357aaecefe1a9dc928ffb9ea807ab8cd0b3abc69e8b5
- Size of remote file:
- 929 kB
- SHA256:
- 4d497cf9775db46ec365d9a5bfb9214b6cef2f0e2e9a8906c59a28785d0fd5d6
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