Instructions to use karths/binary_classification_train_infrastructure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_infrastructure with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_infrastructure")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_infrastructure") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_infrastructure", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4daf8ef8a3a429e7fcffc6c06d14929c821785f895569b532f076a01d002a834
- Size of remote file:
- 657 MB
- SHA256:
- f2b6d3163f37f1ce5fc2d8f0058b0b6cecde30ba1691ca242d06197dc18eeaf0
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