Instructions to use Canstralian/CyberAttackDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Canstralian/CyberAttackDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Canstralian/CyberAttackDetection")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("Canstralian/CyberAttackDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "text": [ | |
| "A vulnerability was discovered in the server software.", | |
| "An SQL injection attack was attempted on the web server.", | |
| "The system is vulnerable to buffer overflow exploitation.", | |
| "Regular server maintenance performed successfully.", | |
| "The user input was sanitized to prevent command injection." | |
| ], | |
| "label": [1, 1, 1, 0, 0] | |
| } | |