XythicK/Mag-Mell-R1-Uncensored-21B-GGUF

Mag-Mell-R1-Uncensored-21B-GGUF

🧠 Model Overview

Mag-Mell-R1-Uncensored-21B-GGUF is a quantized version of Mag-Mell-R1-Uncensored-21B, optimized for efficient inference with reduced memory usage and faster runtime while preserving as much of the original model quality as possible.

This repository provides multiple quantized variants suitable for:

• —Local inference
• —Low-VRAM GPUs
• —CPU-only environments

🔗 Original Model

• —Base model: Mag-Mell-R1-Uncensored-21B
• —Original repository: https://huggingface.co/JustOnion/Mag-Mell-R1-Uncensored-21B
• —Original authors: JustOnion

📦 Quantization Details

• —Quantization method: GGUF
• —Quantization tool: llama.cpp
• —Precision: Mixed (2-8,bit depands in variant)
• —Activation aware: No (weight-only quantinization)
• —Group size: 256 (K-quant variants)

📦 Available Quantized Files

💡 Recommendation: Start with Q4_K_M for the best quality-to-performance ratio.

🚀 Usage Example

llama.cpp

./main -m mag-mell-r1-uncensored-21b-q5_0.gguf -p "The World is beautiful isn't it?" -n 256

Python (llama-cpp-python)

from llama_cpp import Llama

llm = Llama(
    model_path="<MODEL_FILE>.gguf",
    n_ctx=4096,
    n_threads=8
)

print(llm("Your prompt here"))

🙋 Contact

Maintainer: M Mashhudur Rahim [XythicK]

Role: Independent Machine Learning Researcher & Model Infrastructure Maintainer

(Focused on model quantization, optimization, and efficient deployment)

For issues, improvement requests, or additional quantization formats, please use the Hugging Face Discussions or Issues tab.

❤️ Acknowledgements

Thanks to the original model authors for their ongoing contributions to open AI research, and to Hugging Face and the open-source machine learning community for providing the tools and platforms that make efficient model sharing and deployment possible.