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Blog prompts
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# Blog Post Template | ||
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Have I used this template? | ||
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- [ ] Yes | ||
- [ ] No | ||
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This template is designed to help you write blog posts with a clear structure and consistent formatting. Use this as a guide and refine it as needed. | ||
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--- | ||
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## Blog Post Goals | ||
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1. **Project/Topic Overview**: Clearly state what you're writing about and its core purpose. | ||
2. **Personal Takeaways**: Note what you found interesting, useful, or worth remembering. | ||
3. **Value for Others**: Explain why this information would benefit your readers. | ||
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--- | ||
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## Blog Post Composition | ||
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### 1. What Is It? (300 words or less) | ||
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- Provide a concise overview of the topic/project | ||
- Explain the primary functionality or key concepts | ||
- Mention relevant technologies, tools, or frameworks used | ||
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### 2. Why Is It Valuable? (500-1000 words) | ||
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- **Why It's Interesting**: | ||
- Highlight innovative or unique aspects | ||
- Discuss technical achievements or advancements | ||
- Share what caught your attention | ||
- **Why It's Useful**: | ||
- Describe practical applications and use cases | ||
- Identify who benefits from it | ||
- Explain how it solves real problems | ||
- **Why It's Worth Sharing**: | ||
- Technical perspective for developers/experts | ||
- Simplified explanation for beginners | ||
- Impact on the broader community | ||
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### 3. Practical Applications | ||
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- Share specific implementation examples | ||
- Include relevant scenarios for your audience | ||
- Provide actionable steps or recommendations | ||
- Suggest potential integrations or use cases | ||
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--- | ||
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## Markdown Formatting Guidelines | ||
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### Basic Formatting | ||
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1. **Headers** | ||
- Use `#` for main titles (H1) | ||
- Use `##` for sections (H2) | ||
- Use `###` for subsections (H3) | ||
- Leave one blank line before and after headers | ||
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2. **Lists** | ||
- Use `-` for unordered lists | ||
- Use `1.` for ordered lists | ||
- Indent nested lists with 2 spaces | ||
- Leave one blank line before and after lists | ||
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3. **Emphasis** | ||
- Use `**text**` for bold | ||
- Use `*text*` for italics | ||
- Use `***text***` for bold italics | ||
- Use `` `code` `` for inline code | ||
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### Code Blocks | ||
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1. **Fenced Code Blocks** | ||
- Use triple backticks (```) | ||
- Specify language after opening backticks | ||
- Leave one blank line before and after code blocks | ||
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```javascript | ||
function example() { | ||
return 'properly formatted'; | ||
} | ||
``` | ||
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2. **Links and References** | ||
- Use `[text](url)` for inline links | ||
- Use `[text][reference]` with `[reference]: url` for reference-style links | ||
- Group references at the bottom of the document | ||
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### Document Structure | ||
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1. **Spacing** | ||
- Single blank line between paragraphs | ||
- Single blank line before and after lists | ||
- Single blank line before and after code blocks | ||
- No trailing whitespace at line ends | ||
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2. **Line Length** | ||
- Aim for 80 characters per line maximum | ||
- Break long lines at natural points | ||
- Use soft wrapping for paragraphs | ||
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3. **Consistency** | ||
- Use consistent spacing for similar elements | ||
- Maintain consistent list marker styles | ||
- Keep heading hierarchy logical (don't skip levels) | ||
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### Best Practices | ||
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1. **Front Matter** | ||
- Use YAML front matter when needed | ||
- Include metadata like title, date, author | ||
- Separate from content with `---` | ||
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2. **Tables** | ||
- Align table pipes vertically | ||
- Use header separators | ||
- Example: | ||
| Header 1 | Header 2 | | ||
|----------|----------| | ||
| Cell 1 | Cell 2 | | ||
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3. **Images** | ||
- Include alt text: `![alt text](image.jpg)` | ||
- Use relative paths when possible | ||
- Group image references at bottom |
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# GitHub Project Blog Template | ||
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Have I used this template? | ||
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- [ ] Yes | ||
- [ ] No | ||
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--- | ||
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## Blog Post Goals | ||
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1. **Project Overview**: Explore and explain the core purpose and functionality of the GitHub project | ||
2. **Personal Takeaways**: Document innovative aspects and technical achievements | ||
3. **Value for Others**: Share how this project can benefit different types of users | ||
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--- | ||
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### 1. What Is It? | ||
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Provide a concise overview of the GitHub project, including: | ||
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- Core purpose and main functionality | ||
- Key technical features and capabilities | ||
- Technologies and frameworks used | ||
- Deployment and usage options | ||
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### 2. Why Is It Valuable? | ||
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**Why It's Interesting**: | ||
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- Highlight innovative technical approaches | ||
- Note any groundbreaking achievements | ||
- Describe how it advances the field | ||
- Mention notable contributors or backing | ||
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**Why It's Useful**: | ||
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- List key practical applications | ||
- Describe real-world problem-solving capabilities | ||
- Outline deployment flexibility | ||
- Highlight accessibility features | ||
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**Why It's Worth Sharing**: | ||
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- Technical perspective for developers/experts | ||
- Beginner-friendly explanation | ||
- Community impact and possibilities | ||
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### 3. Practical Applications | ||
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Implementation examples: | ||
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- List 3-4 concrete project ideas | ||
- Focus on web/software development use cases | ||
- Consider different scales of implementation | ||
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Integration scenarios: | ||
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- Suggest ways to integrate with existing tools | ||
- List potential platform integrations | ||
- Note compatibility considerations | ||
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Actionable steps: | ||
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1. Installation/setup instructions | ||
2. Basic usage example | ||
3. Next steps for integration | ||
4. Tips for getting started | ||
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## Tags | ||
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An unordered list of category tags for the project. |
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# [Anjok07/ultimatevocalremovergui](https://github.com/Anjok07/ultimatevocalremovergui): AI-Powered Vocal Removal Tool | ||
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## Have I used this template? | ||
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- [ ] Yes | ||
- [x] No | ||
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--- | ||
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## Blog Post Goals | ||
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1. **Project Overview**: Explore Ultimate Vocal Remover GUI, an open-source tool for isolating and removing vocals from audio | ||
2. **Personal Takeaways**: Document the innovative use of multiple AI models for high-quality audio separation | ||
3. **Value for Others**: Share how this technology can benefit music producers, content creators, and audio engineers | ||
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--- | ||
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### 1. What Is It? | ||
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Ultimate Vocal Remover GUI (UVR) is an open-source application that uses state-of-the-art AI models to remove vocals from audio files. Built with Python and PyTorch, it provides an intuitive graphical interface for audio source separation, with custom-trained models developed by the core team. | ||
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Key features: | ||
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- High-quality vocal and instrumental separation | ||
- Multiple AI model options (MDX-Net, Demucs v3/v4) | ||
- GPU acceleration support for faster processing | ||
- Time-stretching and pitch-shifting capabilities | ||
- Cross-platform support (Windows, macOS, Linux) | ||
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### 2. Why Is It Valuable? | ||
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**Why It's Interesting**: | ||
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- Combines multiple cutting-edge AI models for optimal results | ||
- Achieves professional-grade audio separation | ||
- Features custom-trained models by the development team | ||
- Actively maintained with regular updates and improvements | ||
- Strong focus on user-friendly interface and accessibility | ||
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**Why It's Useful**: | ||
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- Creates high-quality instrumental tracks for karaoke/covers | ||
- Enables vocal isolation for remixing and sampling | ||
- Supports various audio processing workflows | ||
- Provides flexible deployment across different platforms | ||
- Free and open-source alternative to commercial solutions | ||
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**Why It's Worth Sharing**: | ||
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- Technical perspective: Demonstrates practical AI application in audio processing | ||
- Beginner-friendly: Makes complex audio separation accessible | ||
- Community impact: Enables creative possibilities for musicians and content creators | ||
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### 3. Practical Applications | ||
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Implementation examples: | ||
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- Create karaoke versions of songs | ||
- Extract vocals for remixing and sampling | ||
- Isolate instruments for music education | ||
- Process audio for content creation | ||
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Integration scenarios: | ||
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- Music production workflows | ||
- Content creation pipelines | ||
- Educational tools | ||
- Live performance preparation | ||
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Actionable steps: | ||
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1. Download the appropriate installer for your platform | ||
2. Install to the main system drive (Windows) or applications folder (macOS) | ||
3. Launch the application and select your preferred AI model | ||
4. Process audio files through the intuitive GUI interface | ||
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## Tags | ||
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- Audio Processing | ||
- Machine Learning | ||
- Deep Learning | ||
- Music Technology | ||
- Python | ||
- Open Source | ||
- AI | ||
- Source Separation | ||
- Audio Engineering | ||
- Music Production | ||
- GUI Application | ||
- Cross Platform |
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