Instructions to use karths/binary_classification_train_build with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_build with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_build")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_build") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_build", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test_top_repo_data.csv from karths/binary_classification_train_build: direct link, hf CLI and curl.
- Browser
- Download file 50.9 MB
-
https://huggingface.co/karths/binary_classification_train_build/resolve/main/test_top_repo_data.csv
- Command line
-
hf download hf://karths/binary_classification_train_build/test_top_repo_data.csv
-
curl -L -o test_top_repo_data.csv https://huggingface.co/karths/binary_classification_train_build/resolve/main/test_top_repo_data.csv
50.9 MB
- Xet hash:
- cd854f539c2ced664676e454032d71846141f0c681795a68cbd3af2d58d36f7d
- Size of remote file:
- 50.9 MB
- SHA256:
- 4fe77360c0dd488094d463febe66cedd8a64e4d29c9124ab100df829aed41804
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