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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 230919069785a3efa49e3e8e4721c8c595c0b443267869e46ee1b64cec849f84
- Size of remote file:
- 331 MB
- SHA256:
- bff767aee86a1dd693be5784534b85d5caba19986655923b5df9ecee7239242d
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