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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 460 Bytes
851e3a7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | import json
from prompts import PROMPTS
def get_prompt(vulnerability_type):
"""
Fetch the prompt for a specific vulnerability type.
"""
return PROMPTS.get(vulnerability_type, "No prompt available for this type.")
def save_results(output, file_name="results.json"):
"""
Save the results to a JSON file.
"""
with open(file_name, "w") as file:
json.dump(output, file, indent=4)
print(f"Results saved to {file_name}")
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