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:
- e9cb9ee2668ea0c01c5ec94ac1aecf98c569ea97203c32fb26920d9e4e6b4994
- Size of remote file:
- 129 MB
- SHA256:
- 7a0aa8468dc3b829458b19a4d2b922757d25a8b949c08163a991a9bcd364283c
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