Instructions to use karths/binary_classification_train_documentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_documentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_documentation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_documentation") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_documentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ccc5013e328842f5e9cf2c9e797fe1fde8b519e46d45016930fd216abc03e996
- Size of remote file:
- 1.06 kB
- SHA256:
- bd8176fd6618dd77e680121cd0ef96d88b28e83690ad66ba643e81bdcada5cb5
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