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:
- 4889a3970391d9b2b5db9bcbc35839e09926767cc31cc53da5d0e781511484c0
- Size of remote file:
- 657 MB
- SHA256:
- 0aa8e106ff517af5c1d1bc699ef9a717aaf448db72149e6363721b905696472d
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