Update README.md

README.md

@@ -10,31 +10,23 @@ Phase 1 Structure Recovery (Skeleton): Transform binary/pseudo-code into obfusca
 Phase 2 Identifier Naming (Skin): Generate human-readable source code with meaningful identifiers 🤗 [HF Link](https://huggingface.co/LLM4Binary/sk2decompile-ident-6.7)
 
 Usage:
-```
-pip install vllm
-apt install clang-format
-#translate the data into reverse_sample.json format
-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-6.7b
-```
 
 0. Install `vllm` and `transformers` via `pip`; install `clang-format` via `apt`.
 1. Prepare a Linux-x64 executable file (ELF).
 2. Use IDA to decompile it (you can also simply use this website: [https://dogbolt.org/](https://dogbolt.org/)).
 3. Convert the data into the corresponding format
    ([https://huggingface.co/LLM4Binary/sk2decompile-struct-6.7b/blob/main/reverse_sample.json](https://huggingface.co/LLM4Binary/sk2decompile-struct-6.7b/blob/main/reverse_sample.json))
+  ```bash
+  python normalize_pseudo.py --input_json reverse_sample.json --output_json reverse_sample.json
+  ```
 4. Run inference:
 
    ```bash
-   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-6.7b
    ```
 
-**Model page:**
-[https://huggingface.co/LLM4Binary/sk2decompile-struct-6.7b](https://huggingface.co/LLM4Binary/sk2decompile-struct-6.7b)
-
 **Project overview:**
 [https://github.com/albertan017/LLM4Decompile/tree/main/sk2decompile](https://github.com/albertan017/LLM4Decompile/tree/main/sk2decompile)