Instructions to use karths/binary_classification_train_automation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_automation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_automation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_automation") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_automation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 421650212ef803b69ab6593e4e18ce6b3e5f7ba9b2ed1e41653b8890531d4662
- Size of remote file:
- 4.66 kB
- SHA256:
- bf482eeb0b7e0710d12909817b70a65658957f44c438feda8e1d4ecb188bfc94
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