🎩 Magicoder: Source Code Is All You Need

🎩 Models | 📚 Dataset | 🚀 Quick Start | 👀 Demo | 📝 Citation | 🙏 Acknowledgements

Important

We are keeping improving the documents and adding more implementation details. Please stay tuned!

About

• 🎩Magicoder is a model family empowered by 🪄OSS-Instruct, a novel approach to enlightening LLMs with open-source code snippets for generating low-bias and high-quality instruction data for code.
• 🪄OSS-Instruct mitigates the inherent bias of the LLM-synthesized instruction data by empowering them with a wealth of open-source references to produce more diverse, realistic, and controllable data.

🎩 Models

Model	Checkpoint	Size	HumanEval (+)	MBPP (+)	Demo	License
Magicoder-CL-7B	🤗 HF Link	7B	60.4 (55.5)	64.2 (52.6)	--	Llama2
Magicoder-S-CL-7B	🤗 HF Link	7B	70.7 (66.5)	68.4 (56.6)	--	Llama2
Magicoder-DS-6.7B	🤗 HF Link	6.7B	66.5 (60.4)	75.4 (61.9)	--	DeepSeek
Magicoder-S-DS-6.7B	🤗 HF Link	6.7B	76.8 (70.7)	75.7 (64.4)	Demo*	DeepSeek

_{*Demo link will expire on 12/8/2023.}

📚 Dataset

• Magicoder-OSS-Instruct-75K: generated through OSS-Instruct using gpt-3.5-turbo-1106 and used to train both Magicoder and Magicoder-S series.
• Magicoder-Evol-Instruct-110K: decontaminated and redistributed from theblackcat102/evol-codealpaca-v1, used to further finetune Magicoder series and obtain Magicoder-S models.

🚀 Quick Start

from transformers import pipeline
import torch

MAGICODER_PROMPT = """You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.

@@ Instruction
{instruction}

@@ Response
"""

instruction = "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."

prompt = MAGICODER_PROMPT.format(instruction=instruction)
generator = pipeline(
    model="ise-uiuc/Magicoder-S-DS-6.7B",
    task="text-generation",
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
result = generator(prompt, max_length=2048, num_return_sequences=1, temperature=0.0)
print(result[0]["generated_text"])

This code snippet will generate the following output:

Here is a simple Python implementation of a TODO list API:

```python
class TodoList:
    def __init__(self):
        self.todo_list = []

    def add_task(self, task):
        if not isinstance(task, str):
            raise ValueError("Task must be a string")
        self.todo_list.append(task)

    def remove_task(self, task):
        if task not in self.todo_list:
            raise ValueError("Task not found in the list")
        self.todo_list.remove(task)

    def get_tasks(self):
        return self.todo_list

    def update_task(self, old_task, new_task):
        if old_task not in self.todo_list:
            raise ValueError("Old task not found in the list")
        if not isinstance(new_task, str):
            raise ValueError("New task must be a string")
        index = self.todo_list.index(old_task)
        self.todo_list[index] = new_task

    def clear_list(self):
        self.todo_list = []
```

This API allows you to add tasks, remove tasks, get all tasks, update tasks, and clear the list. It also raises exceptions for invalid operations.

You can use this API like this:

```python
todo = TodoList()
todo.add_task("Buy groceries")
todo.add_task("Finish project")
print(todo.get_tasks())  # Output: ['Buy groceries', 'Finish project']
todo.update_task("Buy groceries", "Buy fruits")
print(todo.get_tasks())  # Output: ['Buy fruits', 'Finish project']
todo.remove_task("Finish project")
print(todo.get_tasks())  # Output: ['Buy fruits']
todo.clear_list()
print(todo.get_tasks())  # Output: []
```

👀 Demo

We follow WizardCoder and provide the script to build a local demo server with gradio. Refer to /demo for more information.

📝 Citation

@misc{magicoder,
    title={Magicoder: Source Code Is All You Need}, 
    author={Yuxiang Wei and Zhe Wang and Jiawei Liu and Yifeng Ding and Lingming Zhang},
    year={2023},
    eprint={2312.02120},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

🙏 Acknowledgements

• WizardCoder: Evol-Instruct
• DeepSeek-Coder: Base model for Magicoder-DS
• CodeLlama: Base model for Magicoder-CL
• StarCoder: Data decontamination

⚠️ Important Note

• Bias, Risks, and Limitations: Magicoders may sometimes make errors, produce misleading contents, or struggle to manage tasks that are not related to coding.

• Usage: Magicoder models are trained on the synthetic data generated by OpenAI models. Please pay attention to OpenAI's terms of use when using the models and the datasets. Magicoders will not compete with any OpenAI's commercial product.

⭐️ Star History