Instructions to use karths/binary_classification_train_requirement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_requirement with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_requirement")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_requirement") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_requirement", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test_data_for_future_evaluation.csv from karths/binary_classification_train_requirement: direct link, hf CLI and curl.
- Browser
- Download file 16.5 MB
-
https://huggingface.co/karths/binary_classification_train_requirement/resolve/main/test_data_for_future_evaluation.csv
- Command line
-
hf download hf://karths/binary_classification_train_requirement/test_data_for_future_evaluation.csv
-
curl -L -o test_data_for_future_evaluation.csv https://huggingface.co/karths/binary_classification_train_requirement/resolve/main/test_data_for_future_evaluation.csv
16.5 MB
- Xet hash:
- 91514cf9fafdc842054ef6ae9c5b535a86165d10189e9d97c955c51d2d6ef878
- Size of remote file:
- 16.5 MB
- SHA256:
- b56d2a39247149624eba9c7d76c0b9449d9c4b3ef7b1b831cb293a5b5ae62d92
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