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:
- 8406e72d37ddbd2368c587cc3603832871daeb7fc7b55909bbdfad870d22f7c8
- Size of remote file:
- 4.66 kB
- SHA256:
- 86cac2c00747813b4bbd3037c16347abce94f1c04f3fda003b7f9078ae13ee2e
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