Instructions to use karths/binary_classification_train_usab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_usab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_usab")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_usab") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_usab") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c672f9096d586dae7618381aebe61b2109229b724e3b7bcd8342a391183b4f6
- Size of remote file:
- 23.8 MB
- SHA256:
- d948c7b913ba958ed74e4df221b8a100aa14047259b95fc947dc0caf4e938bd7
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