Add Multi-label Classification Examples

## Description
The current examples in the documentation and code samples focus primarily on single-label classification. We need to add more examples that demonstrate multi-label classification capabilities.

## Tasks
- [ ] Add code examples for multi-label classification in the README
- [ ] Create tutorial documentation for multi-label classification use cases
- [ ] Implement example scripts showing both synchronous and asynchronous multi-label classification
- [ ] Add examples of handling and evaluating multi-label predictions
- [ ] Include comparisons between single-label and multi-label approaches
- [ ] Document best practices for multi-label classification prompts

## Expected Result
Comprehensive examples and documentation that clearly demonstrate how to use the library for multi-label classification tasks in different contexts.

## Why is this important?
Multi-label classification is a key feature of the library but currently lacks sufficient examples for users to understand its implementation and usage patterns.

## Difficulty
Easy to Medium - requires understanding of multi-label classification but mostly involves writing examples and documentation