LogPrécis: Unleashing Language Models for Automated Shell Log Analysis
Paper • 2307.08309 • Published
# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("SmartDataPolito/SecureShellBert")
model = AutoModelForMaskedLM.from_pretrained("SmartDataPolito/SecureShellBert")Quick Links
SecureShellBert is a CodeBert model fine-tuned for Masked Language Modelling.
The model was domain-adapted following the Huggingface guide using a corpus of >20k Unix sessions. Such sessions are both malign (see more at HaaS) and benign (see more at NLP2Bash) sessions.
The model was trained:
- For 10 epochs
- mlm probability of 0.15
- batch size = 16
- learning rate of 1e-5
- chunk size = 256
This model was used to finetuned LogPrecis. See more at GitHub for code and data, and please cite our article.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SmartDataPolito/SecureShellBert")