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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bdb9676072c82c8b46d475f2eec0cb4fc3a54c8e5ff1b6e503404ce86245903
- Size of remote file:
- 929 kB
- SHA256:
- ee3b9b6b53f979db88616fe9d30f85c79060bef0f21d5011bb2a88b46178d607
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