--- language: - en license: llama3.1 library_name: transformers tags: - Llama-3.1 - Instruct - loyal AI - GGUF - finetune - chat - gpt4 - synthetic data - roleplaying - unhinged - funny - opinionated - assistant - companion - friend base_model: meta-llama/Llama-3.1-8B-Instruct --- # Dobby-Mini-Unhinged-Llama-3.1-8B_GGUF Dobby-Mini-Unhinged is a compact, high-performance GGUF model based on Llama 3.1 with 8 billion parameters. Designed for efficiency, this model supports quantization levels in **4-bit**, **6-bit**, and **8-bit**, offering flexibility to run on various hardware configurations without compromising performance. ## Compatibility This model is compatible with: - **[LMStudio](https://lmstudio.ai/)**: An easy-to-use desktop application for running and fine-tuning large language models locally. - **[Ollama](https://ollama.com/)**: A versatile tool for deploying, managing, and interacting with large language models seamlessly. ## Quantization Levels | **Quantization** | **Description** | **Use Case** | |------------------|------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------| | **4-bit** | Highly compressed for minimal memory usage. Some loss in precision and quality, but great for lightweight devices with limited VRAM. | Ideal for testing, quick prototyping, or running on low-end GPUs and CPUs. | | **6-bit** | Strikes a balance between compression and quality. Offers improved accuracy over 4-bit without requiring significant additional resources. | Recommended for users with mid-range hardware aiming for a compromise between speed and precision. | | **8-bit** | Full-precision quantization for maximum quality while still optimizing memory usage compared to full FP16 or FP32 models. | Perfect for high-performance systems where maintaining accuracy and precision is critical. | ## Recommended Usage Choose your quantization level based on the hardware you are using: - **4-bit** for ultra-lightweight systems. - **6-bit** for balance on mid-tier hardware. - **8-bit** for maximum performance on powerful GPUs. This model supports prompt fine-tuning for domain-specific tasks, making it an excellent choice for interactive applications like chatbots, question answering, and creative writing.