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:
- a32284e15ad995ff1c9c74570f6a0daa6bc009c7019103513a6f68597ec8a1ee
- Size of remote file:
- 27.5 MB
- SHA256:
- dc736021d43f2a6b45129f7f04e264c2650030eae35f3b441399d7295bbf0c30
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