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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d8c7d6111a47547fa9e5cdc7c26304f50368a2ce69121fdcaab76ad78d6005f
- Size of remote file:
- 657 MB
- SHA256:
- a0b729adc73eab4e69aa52805a32463cfb3e59b90ecd11d27be9e3c3856c5290
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