rdpahalavan/network-packet-flow-header-payload
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How to use rdpahalavan/bert-network-packet-flow-header-payload with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="rdpahalavan/bert-network-packet-flow-header-payload") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("rdpahalavan/bert-network-packet-flow-header-payload")
model = AutoModelForSequenceClassification.from_pretrained("rdpahalavan/bert-network-packet-flow-header-payload")This model was fine-tuned for classifying a network packet into one of the below categories. For details about the dataset used, visit here.
['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']