Instructions to use karths/binary_classification_train_build with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_build with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_build")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_build") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_build", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- caddf87e840d0a9edb070c23a3d82565bdec9a55e3d4972a01d93f0fef49addc
- Size of remote file:
- 657 MB
- SHA256:
- 92cf7d2a0570ddaf4ed1fce57e1b163a5f627b2bdb671321c8cc81aa0da9eb72
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