Instructions to use karths/binary_classification_train_port with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_port with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_port")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_port") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_port") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ffe426741069e5d01c7a6a99231ef9826c78bcfb31d77f3fa235bcb69170b8fc
- Size of remote file:
- 4.66 kB
- SHA256:
- b808ba13205e1570b64421c040c8af0091331fdbcea9ac38211c5dfe852e4018
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