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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c89119d3b9135996ec98eaf7cea605226e17114243524cd5bd663caf39155b46
- Size of remote file:
- 929 kB
- SHA256:
- 44022b48ec3e43b209b5d058a6bc7337f3d3f8fbe5699d1d29bef789c6ec3a22
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