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:
- 6adf34a9a4457bc12c3930bba1a55c88e2c47b88856c87ac23aad169f129048e
- Size of remote file:
- 657 MB
- SHA256:
- 97293b0ee4c4150b50086052e9243e20f2cecbc3f0e254eeb6788d1ba8c8dfa9
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