Instructions to use karths/binary_classification_train_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_test") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test_data_for_future_evaluation.csv from karths/binary_classification_train_test: direct link, hf CLI and curl.
- Browser
- Download file 464 MB
-
https://huggingface.co/karths/binary_classification_train_test/resolve/main/test_data_for_future_evaluation.csv
- Command line
-
hf download hf://karths/binary_classification_train_test/test_data_for_future_evaluation.csv
-
curl -L -o test_data_for_future_evaluation.csv https://huggingface.co/karths/binary_classification_train_test/resolve/main/test_data_for_future_evaluation.csv
464 MB
- Xet hash:
- 0009304bc67884e688f22c55f6ab8f15bb9a88d6b7136f96505bbb6851870e63
- Size of remote file:
- 464 MB
- SHA256:
- eedb7ea66417123a783d5bc84bbdce856a74c78d47cc4be2231e373793a7e16d
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