Instructions to use karths/binary_classification_train_requirement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_requirement with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_requirement")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_requirement") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_requirement", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c338e56b8ffb6335b77e25746c4739007438da88928d54ccc82baf03ec50a72
- Size of remote file:
- 331 MB
- SHA256:
- 742cabf92c08877d71f5cb92a17fcf8f45335f39283100de4165ba7226d73460
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