Lingma SWE-GPT: Software Engineering Large Language Model
Overview
Lingma SWE-GPT is an open-source large language model specifically designed for software engineering tasks. Built upon the foundation of the Qwen series base models, Lingma SWE-GPT has undergone additional training using software engineering development process data to enhance its capabilities in solving complex software engineering tasks.
Model Introduction
Lingma SWE-GPT is a specialized model that focuses on addressing the unique challenges faced in software engineering. By leveraging the robust capabilities of the Qwen base models and incorporating domain-specific knowledge, this model aims to provide intelligent assistance across various aspects of software development.
Model Performance
Lingma SWE-GPT has demonstrated impressive performance in software engineering tasks:
- Achieved a 30.20%(72B) and 18.20%(7B) solution rate on the authoritative SWE-bench Verified leaderboard for software engineering intelligent agents.
- Outperforms other open-source models of similar scale in software engineering-specific tasks.
How to use
Run on SWE-bench
Refer to https://github.com/LingmaTongyi/Lingma-SWE-GPT
Quick Start
from modelscope import AutoModelForCausalLM, AutoTokenizer
model_name = "Lingma/Lingma-SWE-GPT-7B"
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)
prompt = "Give me a short introduction to large language model."
messages = [
{"role": "system", "content": "You are Lingma, created by Tongyi Lingma team. You are a helpful assistant."},
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
generated_ids = model.generate(
**model_inputs,
max_new_tokens=512
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
TODO
Currently only Python is supported. In future updates, we will provide more support for Java, JS/TS and other languages.
License
This project is licensed under the GNU General Public License v2.0 (GPL-2.0).
Contact
For any questions or feedback regarding Lingma SWE-GPT, please contact:
Acknowledgments
We would like to thank the Qwen team for their foundational work, which has been instrumental in the development of Lingma SWE-GPT.
Citation
@article{ma2024understand,
title={How to Understand Whole Software Repository?},
author={Ma, Yingwei and Yang, Qingping and Cao, Rongyu and Li, Binhua and Huang, Fei and Li, Yongbin},
journal={arXiv preprint arXiv:2406.01422},
year={2024}
}