DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored-GGUF
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| License | LLaMA 3.1 |
| Format | GGUF |
| Supported Languages | 11 languages including English, German, French, Italian, Portuguese, Hindi, Spanish, Thai, Chinese, Korean, Japanese |
| Research Paper | Available Here |
What is DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored-GGUF?
This is a quantized version of the DarkIdol-Llama-3.1-8B-Instruct model, specifically optimized for roleplay and creative writing applications. Built on Meta's LLaMA 3.1 architecture, this model has been modified to remove certain restrictions while maintaining high performance across multiple languages and tasks.
Implementation Details
The model utilizes the GGUF format for optimal deployment and has been specifically readjusted to better fulfill various roles, including mobile phone compatibility. It features specialized optimization for roleplay scenarios and creative writing tasks while maintaining the core capabilities of the LLaMA 3.1 architecture.
- Optimized for quick response times and mobile deployment
- Enhanced multilingual support across 11 languages
- Specialized for roleplay and creative writing tasks
- Features uncensored response capabilities
- Built on the LLaMA 3.1 128k context window architecture
Core Capabilities
- Advanced roleplay and character interaction
- Multilingual text generation and understanding
- Creative writing and storytelling
- Scholarly response generation
- Code generation and understanding
- Quick response processing
Frequently Asked Questions
Q: What makes this model unique?
This model combines the powerful LLaMA 3.1 architecture with specialized optimizations for roleplay and creative writing, while removing certain restrictions commonly found in language models. Its GGUF format ensures efficient deployment across various platforms, including mobile devices.
Q: What are the recommended use cases?
The model is particularly well-suited for creative writing, roleplay scenarios, character interaction, and multilingual text generation. It can be effectively used in applications requiring unrestricted creative expression while maintaining high-quality output across multiple languages.
