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Muslim-6B-PRO-GGUF
NightPrince/Muslim-6B-PRO-GGUF
Muslim-6B-PRO-GGUF is a text generation model from NightPrince. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
<p align="center" <img src="https://huggingface.co/NightPrince/Muslim-6B-PRO-GGUF/resolve/main/muslim-6b-pro-banner-light.png" alt="Muslim-6B-PRO" width="100%" / </p
All-time downloads
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Repo size
66.2 GB
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Repo makeup
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.gguf66.2 GB · 100%
At a glance
- Task
- Text Generation
- License
- apache-2.0
- Access
- Public
- Created
- Jul 22, 2026
- Updated
- Jul 22, 2026
- SHA
- 5415787a
Base models
Model card
From the Hugging Face model README
<p align="center">
<img src="https://huggingface.co/NightPrince/Muslim-6B-PRO-GGUF/resolve/main/muslim-6b-pro-banner-light.png" alt="Muslim-6B-PRO" width="100%" />
</p>
Muslim-6B-PRO — GGUF
GGUF quantizations of NightPrince/Muslim-6B-PRO
for local inference with llama.cpp and compatible
runtimes (LM Studio, Ollama, koboldcpp, etc.).
Files
| File | Quant | Size | Notes |
|---|---|---|---|
Muslim-6B-PRO-Q2_K.gguf | Q2_K | 2.26 GB | Smallest, largest quality loss |
Muslim-6B-PRO-Q3_K_S.gguf | Q3_K_S | 2.57 GB | |
Muslim-6B-PRO-Q3_K_M.gguf | Q3_K_M | 2.83 GB | |
Muslim-6B-PRO-Q3_K_L.gguf | Q3_K_L | 3.06 GB | |
Muslim-6B-PRO-Q4_0.gguf | Q4_0 | 3.24 GB | Legacy 4-bit |
Muslim-6B-PRO-Q4_1.gguf | Q4_1 | 3.56 GB | Legacy 4-bit |
Muslim-6B-PRO-Q4_K_S.gguf | Q4_K_S | 3.26 GB | |
Muslim-6B-PRO-Q4_K_M.gguf | Q4_K_M | 3.41 GB | Recommended default — best size/quality balance |
Muslim-6B-PRO-Q5_0.gguf | Q5_0 | 3.88 GB | Legacy 5-bit |
Muslim-6B-PRO-Q5_1.gguf | Q5_1 | 4.19 GB | Legacy 5-bit |
Muslim-6B-PRO-Q5_K_S.gguf | Q5_K_S | 3.88 GB | |
Muslim-6B-PRO-Q5_K_M.gguf | Q5_K_M | 3.96 GB | Near-lossless, good balance for more headroom |
Muslim-6B-PRO-Q6_K.gguf | Q6_K | 4.55 GB | Very close to F16 quality |
Muslim-6B-PRO-Q8_0.gguf | Q8_0 | 5.89 GB | Near-lossless |
Muslim-6B-PRO-f16.gguf | F16 | 11.08 GB | Full precision, no quantization loss |
Usage
llama.cpp
llama-cli -hf NightPrince/Muslim-6B-PRO-GGUF:Q4_K_M -p "السلام عليكم"
or, with a locally downloaded file:
llama-cli -m Muslim-6B-PRO-Q4_K_M.gguf -p "السلام عليكم"
Server mode (OpenAI-compatible API)
llama-server -m Muslim-6B-PRO-Q4_K_M.gguf --port 8080
Tool calling
This model uses the Hermes-style <tool_call> format. llama-server supports this natively via
its --jinja flag (uses the model's built-in chat template) combined with the standard
OpenAI-style tools parameter in requests.
Choosing a quant
- Q4_K_M is the recommended default for most use — the standard "good enough for almost everyone" tradeoff.
- Go Q5_K_M or Q6_K if you have the VRAM/RAM headroom and want output closer to the original fp16 model, especially for tool-call argument precision.
- Go Q2_K/Q3_K only under tight memory constraints — expect noticeably more degradation on precise tasks like tool-call JSON formatting and exact surah/ayah references.
- Q8_0 or F16 for maximum fidelity when memory isn't a constraint.
Related resources
- Full-precision model card, training details, and dataset: NightPrince/Muslim-6B-PRO
- Live demo with real tool-calling (ZeroGPU): NightPrince/muslim-6b-pro-demo
- Fine-tuning code: github.com/NightPrinceY/Karnak-6B-Finetuning
- Task
- Text Generation
- License
- apache-2.0
- Languages
- ar, en
- Created
- Jul 22, 2026
- Updated
- Jul 22, 2026