Instructions to use karths/binary_classification_train_build with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_build with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_build")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_build") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_build") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf2bdb38cd4016eeee85ac3785caa31bddc4e85c5d9237c69104e48572cbb72d
- Size of remote file:
- 849 MB
- SHA256:
- fd150f0b5bda48f425f8e1b9f4696b7ea437ff7ecda7e84d25dd31c55c0880f0
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