Instructions to use karths/binary_classification_train_process with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_process with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_process")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_process") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_process") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0bce35f30540287b88d96521ffa0209b2d02e27285546742f45a785ae4674a96
- Size of remote file:
- 4.66 kB
- SHA256:
- b52d64e4bc5cdefe9f99e05e2810b09bbf42daae2d5851045d78cb5b1eaf5eac
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