Instructions to use karths/binary_classification_train_secu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_secu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_secu")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_secu") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_secu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from karths/binary_classification_train_secu: direct link, hf CLI and curl.
- Browser
- Download file 328 MB
-
https://huggingface.co/karths/binary_classification_train_secu/resolve/main/model.safetensors
- Command line
-
hf download hf://karths/binary_classification_train_secu/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/karths/binary_classification_train_secu/resolve/main/model.safetensors
328 MB
- Xet hash:
- b2a168ab953f1e23606b23ab1308d89adb46e6644eca5fa456ecc52bebcdebe4
- Size of remote file:
- 328 MB
- SHA256:
- a204cb2ed2d838286975c12d7daff1cc3562a5dc95d8d4c6917a2fd61c670315
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