Instructions to use karths/binary_classification_train_perf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_perf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_perf")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_perf") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_perf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test_top_repo_data.csv from karths/binary_classification_train_perf: direct link, hf CLI and curl.
- Browser
- Download file 14.6 MB
-
https://huggingface.co/karths/binary_classification_train_perf/resolve/main/test_top_repo_data.csv
- Command line
-
hf download hf://karths/binary_classification_train_perf/test_top_repo_data.csv
-
curl -L -o test_top_repo_data.csv https://huggingface.co/karths/binary_classification_train_perf/resolve/main/test_top_repo_data.csv
14.6 MB
- Xet hash:
- 99307464f8a606feb501e23946b27299e97ab8bf27be26b6abd833f42e89eb75
- Size of remote file:
- 14.6 MB
- SHA256:
- 7df536c5b46d2b767e42ecea0b608c2a6a55bb3822323556bd94c2c565db0b57
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