| --- |
| library_name: peft |
| base_model: WizardLMTeam/WizardCoder-Python-13B-V1.0 |
| license: apache-2.0 |
| --- |
| |
| # Model Card for Model ID |
|
|
| This is a model capable of injecting bugs into correct Python programs. It was used to inject bugs into correct programs to form the core of the MegaBugFix benchmark. |
|
|
|
|
| ## Model Details |
|
|
| - **Developed by:** Balázs Szalontai |
| - **Model type:** Decoder-only Language Model |
| - **Language(s) (NLP):** None |
| - **License:** Apache license 2.0 |
| - **Finetuned from model [optional]:** WizardLMTeam/WizardCoder-Python-13B-V1.0 |
|
|
| ## Uses |
|
|
| You may use the model in the following way: |
|
|
| ```python |
| import torch |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| from peft import PeftModel |
| import re |
| |
| model_id_pretrained = 'WizardLMTeam/WizardCoder-Python-13B-V1.0' |
| model_id_finetuned = 'szalontaib/MegaBugInject' |
| |
| tokenizer = AutoTokenizer.from_pretrained(model_id_pretrained, add_eos_token=False) |
| model = AutoModelForCausalLM.from_pretrained(model_id_pretrained, device_map='auto', dtype=torch.float16, trust_remote_code=True) |
| model = PeftModel.from_pretrained(model, model_id_finetuned) |
| |
| |
| def extract_diff(model_output): |
| pattern = re.compile(r'\s*\[DIFF\](.*?)\[/DIFF\]\s*', re.DOTALL) |
| matches = pattern.findall(model_output) |
| if matches: |
| return matches[0].strip('\n') |
| return None |
| |
| def diff2code(diff : str) -> str: |
| return '\n'.join( |
| line[2:] for line in diff.splitlines() |
| if not line.startswith('-') |
| ).strip() |
| |
| def corrupt(program, model, tokenizer, **generation_kwargs): |
| prompt = f'[PYTHON]\n{program.strip()}\n[/PYTHON]\n[DIFF]\n' |
| model_inputs = tokenizer([prompt], return_tensors="pt").to(model.device) |
| generated_ids = model.generate(**model_inputs, **generation_kwargs) |
| outputs = tokenizer.batch_decode(generated_ids, skip_special_tokens=True) |
| diffs = [extract_diff(output) for output in outputs] |
| corrupted_programs = [diff2code(diff) for diff in diffs if diff is not None] |
| return corrupted_programs |
| |
| |
| test_code = ''' |
| def bitcount(n): |
| count = 0 |
| while n: |
| n &= n - 1 |
| count += 1 |
| return count |
| '''.strip() |
| |
| corrupted_programs = corrupt( |
| test_code, model, tokenizer, |
| do_sample=True, |
| temperature=0.5, |
| max_new_tokens=4096, |
| num_return_sequences=5, |
| ) |
| |
| for corrupted_program in corrupted_programs: |
| print('-'*30) |
| print(corrupted_program) |
| ``` |
|
|
| # Citation |
|
|
| If you use our benchmark or bug injection model, please cite our paper. |
|
|
| ``` |
| @misc{szalontai2026diffbasedcodecorruptionusing, |
| title={Diff-Based Code Corruption using LLMs for Large-Scale Bugfix Benchmarking}, |
| author={Balázs Szalontai and Ábel Szauter and Balázs Márton and Péter Verebics and Balázs Pintér and Tibor Gregorics}, |
| year={2026}, |
| eprint={2606.29088}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.SE}, |
| url={https://arxiv.org/abs/2606.29088}, |
| } |
| ``` |
