Instructions to use karths/binary_classification_train_TD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_TD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_TD")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_TD") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_TD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d8d23c0ad1f34ae3bb7d34ae32d154989584887454e5cc30307f71ee880a716
- Size of remote file:
- 331 MB
- SHA256:
- 89afbea02c996dd85e9d20fd30c606869971818d3269e2aec8f81f3f527094ed
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