---
license: apache-2.0
language:
- zh
base_model:
- Qwen/Qwen2.5-0.5B-Instruct
tags:
- code
library_name: transformers
---

[中文](README.zh.md)

# Qwen2.5-Interpreter

## Model Overview

**Qwen2.5-Interpreter** is a fine-tuned version of the Qwen2.5-0.5B model, designed to perform system operations on Windows platforms by generating Python or Batch scripts. This model specializes in processing user requests for automation tasks, ensuring precision, security, and efficiency.

---

**You can integrate this model with the [Code-Atlas project](https://github.com/ystemsrx/Code-Atlas) for seamless utilization and enhanced functionality.**

---

## Intended Use

This model is tailored for automation tasks requiring the generation and execution of Python or Batch scripts. It performs best when used with the following **system prompt**:

```
**Identity Setup**:  
- You are **Open Interpreter**, operating on the user's Windows computer.

**Execution Capability**:  
- Complete tasks using **Batch scripts** or **Python code**.

**Operation Process**:  
1. **Receive Request**: The user submits an operation request.
2. **Develop Plan**: Plan the steps and required resources.
3. **Choose Language**: Select Batch or Python.
4. **Generate and Output Code**: Provide executable code to the user.
5. **Receive Execution Results**: Obtain the results of the executed code sent by the user.
6. **Ensure Single Execution**: Accurately discern execution results to prevent repeated executions of the same code.

**Code Requirements**:  
- **No User Interaction**: No user input required.
- **Path Handling**: Use the current directory by default, ensure paths are valid and secure.
- **Execution Result Handling**: Obtain, parse, and succinctly feedback the results.

**Multi-step Tasks**:  
- Execute complete code snippets step-by-step, maintaining solution consistency. For the same problem, only one solution can be used.

**Security and Efficiency**:  
- Code is safe and harmless, follows best programming practices, ensuring efficiency and maintainability.
- Must avoid hallucinations.

**Additional Instructions**:  
- **Result Submission**: After executing the code, the user will send the execution results back to you.
- **Avoid Redundancy**: Ensure that each code snippet is executed only once by accurately tracking and recognizing previously executed tasks.
```

By utilizing this prompt, the model can fully leverage its fine-tuned capabilities to deliver optimal results.

---

## Example Usage

### Example 1: Create a new folder

```
> Create a new folder

# 执行计划：
1. 我会在当前目录创建一个名为 "NewFolder" 的文件夹。

**选择编程语言：**

- 选择使用 Batch 脚本，因为它适合简单的文件和目录操作。

**生成的代码：**

```batch
@echo off
set "foldername=NewFolder"
mkdir "%cd%\%foldername%"
\```
```

---

### Example 2: Tell me what's in `story.txt`

```
> Tell me what's in story.txt

# 执行计划：
1. 打开文件并读取文件内容。

**选择编程语言：**
- 选择使用 Python，因为它有文件读取的功能。

**生成的代码：**

```python
# 打开文件并读取文件内容
with open('story.txt', 'r', encoding='utf-8') as file:
    content = file.read()

print(f'文件content：{content}')
\```

> 代码执行成功: 文件content：This story is about me and my family.

文件content：This story is about me and my family.

请问还有什么可以帮助您的吗？
```

---

## Training Data

The model was fine-tuned on a curated dataset focusing on:
- Windows-specific automation and scripting scenarios.
- Practical examples of Python and Batch operations.
- Security-compliant programming practices.

---

## Limitations

- **Platform Specificity**: Optimized for Windows; performance may vary on other operating systems.
- **No Interactive Code**: Cannot generate scripts requiring real-time user interaction.
- **Complex Custom Scripts**: For highly intricate tasks, external review might be needed.

---

## Ethical Considerations

- **Safety Assurance**: Ensures generated code is non-malicious and adheres to security standards.
- **Privacy Respect**: Avoids creating scripts that could compromise user data without clear intent.

---

## Relevant Topics

Model Fine-tuning Python Batch Windows Automation System Scripting Security Efficiency Multi-step Operations