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:
- 92955c1a1b3dc26b5888bf16179b6be4df47ea836a66c2058637bed58f80740a
- Size of remote file:
- 34.1 MB
- SHA256:
- 5adc72120c0ab5d993faaa58eb13ce09f017f84bfe2c1e3d747e1394ff133a77
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