Instructions to use karths/binary_classification_train_comp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_comp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_comp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_comp") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_comp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95931e012f27f6969a592302cc9d84e31f530f3a76f468c8c9442a4b6d9d3255
- Size of remote file:
- 5.18 kB
- SHA256:
- e2f49eaa4bc8e46aafa72cc70e2c03820d95ffde8da5b6d004aa8848152170c2
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