Instructions to use karths/binary_classification_train_usab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_usab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_usab")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_usab") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_usab") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61203f386b3078da2fdb89a788aaac46f4caf17238b67a2ff91622f44794678f
- Size of remote file:
- 4.66 kB
- SHA256:
- 1a6905c365b426a1e0a4d3d61f224c7b790939e60a4343b9346c925f1e81fb59
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