Instructions to use mahwizzzz/NID_tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahwizzzz/NID_tr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mahwizzzz/NID_tr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mahwizzzz/NID_tr") model = AutoModelForSequenceClassification.from_pretrained("mahwizzzz/NID_tr") - Notebooks
- Google Colab
- Kaggle
This model was fine-tuned for classifying a network packet into one of the below categories.
['Analysis',
'Backdoor',
'Bot',
'DDoS',
'DoS',
'DoS GoldenEye',
'DoS Hulk',
'DoS SlowHTTPTest',
'DoS Slowloris',
'Exploits',
'FTP Patator',
'Fuzzers',
'Generic',
'Heartbleed',
'Infiltration',
'Normal',
'Port Scan',
'Reconnaissance',
'SSH Patator',
'Shellcode',
'Web Attack - Brute Force',
'Web Attack - SQL Injection',
'Web Attack - XSS',
'Worms']
- Downloads last month
- 1