Instructions to use karths/binary_classification_train_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_main")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_main") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_main", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75de1916f91e6560f71c166be9820c26ca6490f1b5e78084abfb2c749bb06b80
- Size of remote file:
- 331 MB
- SHA256:
- 714ac91b6339c053d4af144c82dd1285c9de4de5dea375bb1a3858cc5f189470
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