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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90992460bf9a965bac95d4f500c4d4c0fdb082de710f81ec376854e9d3a7a260
- Size of remote file:
- 1.06 kB
- SHA256:
- 71ae05b0103f90146ce39046375ae878319f4c7d09227e8bc0c984a5fcb5bda2
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