Instructions to use karths/binary_classification_train_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_main")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_main") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_main", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13be4d76248bdb54bd026011104235ae419efe4794895776395ba879128125f3
- Size of remote file:
- 328 MB
- SHA256:
- f25d2bafc473f688ff88ab0a0faebe904efb295ebf8c6ef9f1d04b6e5fdfe6ec
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