Instructions to use karths/binary_classification_train_usab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_usab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_usab")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_usab") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_usab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test_data_for_future_evaluation.csv from karths/binary_classification_train_usab: direct link, hf CLI and curl.
- Browser
- Download file 23.8 MB
-
https://huggingface.co/karths/binary_classification_train_usab/resolve/bf73d26480d615feafcb400aeacdb31d09bb2888/test_data_for_future_evaluation.csv
- Command line
-
hf download hf://karths/binary_classification_train_usab@bf73d26480d615feafcb400aeacdb31d09bb2888/test_data_for_future_evaluation.csv
-
curl -L -o test_data_for_future_evaluation.csv https://huggingface.co/karths/binary_classification_train_usab/resolve/bf73d26480d615feafcb400aeacdb31d09bb2888/test_data_for_future_evaluation.csv
23.8 MB
- Xet hash:
- 1c672f9096d586dae7618381aebe61b2109229b724e3b7bcd8342a391183b4f6
- Size of remote file:
- 23.8 MB
- SHA256:
- d948c7b913ba958ed74e4df221b8a100aa14047259b95fc947dc0caf4e938bd7
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