| license: mit | |
| pipeline_tag: text-generation | |
| library_name: transformers | |
| # SK²Decompile: Structure Recovery Model | |
| This repository contains the `sk2decompile-struct-6.7b` model, which is part of the SK²Decompile framework introduced in the paper [Decompile-Bench: Million-Scale Binary-Source Function Pairs for Real-World Binary Decompilation](https://huggingface.co/papers/2505.12668). | |
| The full codebase and more details can be found on the [GitHub repository](https://github.com/albertan017/LLM4Decompile). | |
| SK²Decompile is a novel two-phase framework for binary decompilation using Large Language Models (LLMs). Our approach decomposes the complex decompilation task into two manageable phases: | |
| Phase 1 Structure Recovery (Skeleton): Transform binary/pseudo-code into obfuscated intermediate representations (current model) | |
| Phase 2 Identifier Naming (Skin): Generate human-readable source code with meaningful identifiers 🤗 [HF Link](https://huggingface.co/LLM4Binary/sk2decompile-ident-6.7) | |
| Usage: | |
| ``` | |
| python normalize_pseudo.py --input_json reverse_sample.json --output_json reverse_sample.json | |
| python sk2decompile.py --dataset_path reverse_sample.json --model_path LLM4Binary/sk2decompile-struct-6.7b --recover_model_path LLM4Binary/sk2decompile-ident-6.7 | |
| ``` |