Instructions to use karths/binary_classification_train_infrastructure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_infrastructure with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_infrastructure")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_infrastructure") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_infrastructure") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cc1cde3a18f913ed7ec0f07ddf61c191dc8c7c691820d491e921a6ee701b929
- Size of remote file:
- 930 kB
- SHA256:
- 3b7c5d1211924318e8a098239eb291523d20bf1205b4e3f2f9db9967950b4645
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