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---
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
``` |