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---
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.
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