This is an open collection of methodologies, tools and step by step instructions to help with successful training and fine-tuning of large language models and multi-modal models and their inference.

Abstract: Large language models have catalyzed an unprece-dented wave in code generation. While achieving significant advances, they blur the distinctions between machine- and human-authored source ...

Abstract: This paper compares synthetic and real-world code datasets for machine learning applications in cybersecurity by examining the relationships between machine code and Low-Level Virtual ...