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Model: ystemsrx/Qwen2.5-Interpreter Source: Original Platform
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Qwen2.5-0.5b-interpreter-f16.gguf
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Qwen2.5-0.5b-interpreter-f16.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:1ca5c7357d04eaf9f0f50d8ad6c17037c8ceeacef0a598cd5b9dd88137fc7ce9
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size 994154432
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README.md
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README.md
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---
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license: apache-2.0
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language:
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- zh
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base_model:
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- Qwen/Qwen2.5-0.5B-Instruct
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tags:
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- code
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library_name: transformers
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---
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[中文](README.zh.md)
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# Qwen2.5-Interpreter
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## Model Overview
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**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.
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---
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**You can integrate this model with the [Code-Atlas project](https://github.com/ystemsrx/Code-Atlas) for seamless utilization and enhanced functionality.**
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---
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## Intended Use
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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**:
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```
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**Identity Setup**:
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- You are **Open Interpreter**, operating on the user's Windows computer.
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**Execution Capability**:
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- Complete tasks using **Batch scripts** or **Python code**.
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**Operation Process**:
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1. **Receive Request**: The user submits an operation request.
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2. **Develop Plan**: Plan the steps and required resources.
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3. **Choose Language**: Select Batch or Python.
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4. **Generate and Output Code**: Provide executable code to the user.
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5. **Receive Execution Results**: Obtain the results of the executed code sent by the user.
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6. **Ensure Single Execution**: Accurately discern execution results to prevent repeated executions of the same code.
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||||
|
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**Code Requirements**:
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- **No User Interaction**: No user input required.
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- **Path Handling**: Use the current directory by default, ensure paths are valid and secure.
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- **Execution Result Handling**: Obtain, parse, and succinctly feedback the results.
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|
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**Multi-step Tasks**:
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- Execute complete code snippets step-by-step, maintaining solution consistency. For the same problem, only one solution can be used.
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**Security and Efficiency**:
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- Code is safe and harmless, follows best programming practices, ensuring efficiency and maintainability.
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- Must avoid hallucinations.
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|
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**Additional Instructions**:
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- **Result Submission**: After executing the code, the user will send the execution results back to you.
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- **Avoid Redundancy**: Ensure that each code snippet is executed only once by accurately tracking and recognizing previously executed tasks.
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```
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By utilizing this prompt, the model can fully leverage its fine-tuned capabilities to deliver optimal results.
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---
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## Example Usage
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### Example 1: Create a new folder
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```
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> Create a new folder
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# 执行计划：
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1. 我会在当前目录创建一个名为 "NewFolder" 的文件夹。
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**选择编程语言：**
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|
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- 选择使用 Batch 脚本，因为它适合简单的文件和目录操作。
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**生成的代码：**
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||||
```batch
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@echo off
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set "foldername=NewFolder"
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mkdir "%cd%\%foldername%"
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\```
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```
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---
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### Example 2: Tell me what's in `story.txt`
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```
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> Tell me what's in story.txt
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# 执行计划：
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1. 打开文件并读取文件内容。
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**选择编程语言：**
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- 选择使用 Python，因为它有文件读取的功能。
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**生成的代码：**
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```python
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# 打开文件并读取文件内容
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with open('story.txt', 'r', encoding='utf-8') as file:
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content = file.read()
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print(f'文件content：{content}')
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\```
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> 代码执行成功: 文件content：This story is about me and my family.
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文件content：This story is about me and my family.
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||||
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||||
请问还有什么可以帮助您的吗？
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||||
```
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||||
|
||||
---
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## Training Data
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The model was fine-tuned on a curated dataset focusing on:
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- Windows-specific automation and scripting scenarios.
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- Practical examples of Python and Batch operations.
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- Security-compliant programming practices.
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|
||||
---
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||||
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## Limitations
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||||
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||||
- **Platform Specificity**: Optimized for Windows; performance may vary on other operating systems.
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||||
- **No Interactive Code**: Cannot generate scripts requiring real-time user interaction.
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- **Complex Custom Scripts**: For highly intricate tasks, external review might be needed.
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|
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---
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## Ethical Considerations
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- **Safety Assurance**: Ensures generated code is non-malicious and adheres to security standards.
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- **Privacy Respect**: Avoids creating scripts that could compromise user data without clear intent.
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|
||||
---
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## Relevant Topics
|
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|
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Model Fine-tuning Python Batch Windows Automation System Scripting Security Efficiency Multi-step Operations
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154
README.zh.md
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154
README.zh.md
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[English](README.md)
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|
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# Qwen2.5-Interpreter
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## 模型概述
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||||
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||||
**Qwen2.5-Interpreter** 是基于 Qwen2.5-0.5B 微调的模型，专为执行自然语言操作任务而设计。用户可以通过自然语言描述需求，该模型会将请求解析为 Python 或 Batch 脚本，并在 Windows 系统上执行相关操作。模型特别擅长自动化任务，确保操作的安全性、精确性和高效性。
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|
||||
---
|
||||
|
||||
**你可以结合[Code-Atlas项目](https://github.com/ystemsrx/Code-Atlas)使用本模型，实现便捷的集成与功能扩展。**
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|
||||
---
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||||
|
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## 适用场景
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||||
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||||
本模型专为自然语言驱动的自动化任务而设计。用户可以通过日常语言描述操作需求，模型会自动解析、规划并生成可执行脚本。在以下 **系统提示词** 配合下，模型能达到最佳表现：
|
||||
|
||||
```
|
||||
**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.
|
||||
```
|
||||
|
||||
通过上述提示词，用户可以充分利用模型的能力，以自然语言完成复杂任务。
|
||||
|
||||
---
|
||||
|
||||
## 示例用法
|
||||
|
||||
### 示例 1: 创建一个新文件夹
|
||||
|
||||
```
|
||||
> 创建文件夹
|
||||
|
||||
# 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%"
|
||||
\```
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 示例 2: 读取 `story.txt` 文件的内容
|
||||
|
||||
```
|
||||
> story.txt中有什么
|
||||
|
||||
# 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'文件内容：{content}')
|
||||
\```
|
||||
|
||||
> 代码执行成功: 文件内容：This story is about me and my family.
|
||||
|
||||
文件内容：This story is about me and my family.
|
||||
|
||||
请问还有什么可以帮助您的吗？
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 自然语言交互
|
||||
|
||||
本模型能够根据自然语言描述执行以下任务：
|
||||
- **文件管理**: 例如“创建一个名为 Reports 的文件夹”或“删除所有 .log 文件”。
|
||||
- **系统诊断**: 例如“检查可用磁盘空间”或“显示运行的进程”。
|
||||
- **任务自动化**: 例如“备份我的 Documents 文件夹”或“运行清理临时文件的脚本”。
|
||||
|
||||
---
|
||||
|
||||
## 训练数据
|
||||
|
||||
该模型通过以下数据集微调：
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||||
- 包含 Windows 系统特定命令的自然语言描述。
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||||
- 包括 Python 和 Batch 的脚本操作实例。
|
||||
- 强调安全、高效的编码实践，确保生成脚本的可靠性。
|
||||
|
||||
---
|
||||
|
||||
## 性能与基准测试
|
||||
|
||||
- **自然语言理解**: 能够高精度地将用户需求解析为可执行脚本。
|
||||
- **代码生成精确度**: 保证生成的代码准确且可执行。
|
||||
- **任务多样性支持**: 可适配广泛的系统操作需求。
|
||||
|
||||
---
|
||||
|
||||
## 限制
|
||||
|
||||
- **平台限制**: 模型针对 Windows 优化，在其他操作系统上可能表现有限。
|
||||
- **非交互式脚本**: 无法生成或运行需要用户实时输入的脚本。
|
||||
- **复杂逻辑支持有限**: 对于高度复杂的任务可能需要额外验证。
|
||||
|
||||
---
|
||||
|
||||
## 道德考量
|
||||
|
||||
- **安全性**: 生成的代码始终安全，无恶意指令。
|
||||
- **隐私保护**: 避免在未明确要求的情况下生成可能泄露用户数据的代码。
|
||||
- **透明性**: 在生成代码前明确告知计划和逻辑，保证用户知情。
|
||||
|
||||
---
|
||||
|
||||
## 相关话题
|
||||
|
||||
自然语言处理 自动化 Python Batch Windows 脚本 安全 系统操作 人机交互
|
||||
24
added_tokens.json
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24
added_tokens.json
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|
||||
{
|
||||
"</tool_call>": 151658,
|
||||
"<tool_call>": 151657,
|
||||
"<|box_end|>": 151649,
|
||||
"<|box_start|>": 151648,
|
||||
"<|endoftext|>": 151643,
|
||||
"<|file_sep|>": 151664,
|
||||
"<|fim_middle|>": 151660,
|
||||
"<|fim_pad|>": 151662,
|
||||
"<|fim_prefix|>": 151659,
|
||||
"<|fim_suffix|>": 151661,
|
||||
"<|im_end|>": 151645,
|
||||
"<|im_start|>": 151644,
|
||||
"<|image_pad|>": 151655,
|
||||
"<|object_ref_end|>": 151647,
|
||||
"<|object_ref_start|>": 151646,
|
||||
"<|quad_end|>": 151651,
|
||||
"<|quad_start|>": 151650,
|
||||
"<|repo_name|>": 151663,
|
||||
"<|video_pad|>": 151656,
|
||||
"<|vision_end|>": 151653,
|
||||
"<|vision_pad|>": 151654,
|
||||
"<|vision_start|>": 151652
|
||||
}
|
||||
28
config.json
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28
config.json
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|
||||
{
|
||||
"_name_or_path": "Qwen2.5-0.5B-Instruct",
|
||||
"architectures": [
|
||||
"Qwen2ForCausalLM"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 896,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 4864,
|
||||
"max_position_embeddings": 32768,
|
||||
"max_window_layers": 21,
|
||||
"model_type": "qwen2",
|
||||
"num_attention_heads": 14,
|
||||
"num_hidden_layers": 24,
|
||||
"num_key_value_heads": 2,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.44.2",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
14
generation_config.json
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14
generation_config.json
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|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
||||
"repetition_penalty": 1.1,
|
||||
"temperature": 0.7,
|
||||
"top_k": 20,
|
||||
"top_p": 0.8,
|
||||
"transformers_version": "4.44.2"
|
||||
}
|
||||
151388
merges.txt
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151388
merges.txt
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File diff suppressed because it is too large
Load Diff
3
model.safetensors
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3
model.safetensors
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||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:cfdb75b3a80b9c2b64d30ae47026f7d4870e0dc151a2dd774a7ca40a07fc3fc5
|
||||
size 988097824
|
||||
31
special_tokens_map.json
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special_tokens_map.json
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|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
303283
tokenizer.json
Normal file
303283
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
208
tokenizer_config.json
Normal file
208
tokenizer_config.json
Normal file
@@ -0,0 +1,208 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{% set system_message = 'You are a helpful assistant.' %}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}{% if system_message is defined %}{{ '<|im_start|>system\n' + system_message + '<|im_end|>\n' }}{% endif %}{% for message in loop_messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|im_start|>user\n' + content + '<|im_end|>\n<|im_start|>assistant\n' }}{% elif message['role'] == 'assistant' %}{{ content + '<|im_end|>' + '\n' }}{% endif %}{% endfor %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user