Instructions to use void-gryph/cyberrealistic-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use void-gryph/cyberrealistic-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="void-gryph/cyberrealistic-GGUF",
	filename="cyberrealistic.Q4_K_M.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use void-gryph/cyberrealistic-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf void-gryph/cyberrealistic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf void-gryph/cyberrealistic-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf void-gryph/cyberrealistic-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf void-gryph/cyberrealistic-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf void-gryph/cyberrealistic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf void-gryph/cyberrealistic-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf void-gryph/cyberrealistic-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf void-gryph/cyberrealistic-GGUF:Q4_K_M

Use Docker

docker model run hf.co/void-gryph/cyberrealistic-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use void-gryph/cyberrealistic-GGUF with Ollama:
```
ollama run hf.co/void-gryph/cyberrealistic-GGUF:Q4_K_M
```

Unsloth Studio new

How to use void-gryph/cyberrealistic-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for void-gryph/cyberrealistic-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for void-gryph/cyberrealistic-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for void-gryph/cyberrealistic-GGUF to start chatting

Docker Model Runner
How to use void-gryph/cyberrealistic-GGUF with Docker Model Runner:
```
docker model run hf.co/void-gryph/cyberrealistic-GGUF:Q4_K_M
```

Lemonade

How to use void-gryph/cyberrealistic-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull void-gryph/cyberrealistic-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.cyberrealistic-GGUF-Q4_K_M

List all available models

lemonade list

CyberRealistic - GGUF Ultimate Edition 🏭

Este repositorio ofrece la colección en formato GGUF del modelo original CyberRealistic. Optimizados para inferencia con poca memoria.

� Tabla de Comparativa de Cuantizaciones

Versión	Tipo	Peso	Calidad	Uso Recomendado
Q4_K_M	Medium	~5-7GB	Basica	Balance / Velocidad
Q5_K_M	Large	~8-10GB	Alta	Calidad
Q8_0	Ultra	Original	Alta	Calidad

⚙️ Guía de Optimización y Comparativa de Parámetros

Para obtener los mejores resultados con esta versión GGUF, se recomiendan los siguientes ajustes:

1. 🎚️ Comparativa de CFG (Classifier Free Guidance)

CFG Scale	Efecto en GGUF	Resultado Visual
1.0 - 3.5	Suave / Realista	Menos contraste, ideal para estilos fotográficos.
4.0 - 6.5	Recomendado	Balance perfecto entre fidelidad al prompt y detalle.
7.0 - 9.0	Estilizado	Colores más saturados y bordes más definidos.

2. ⚡ Comparativa de Pasos (Sampling Steps)

Pasos	Rendimiento	Nivel de Detalle
15 - 20	Ultra Rápido	Bocetos rápidos o previsualizaciones.
25 - 35	Óptimo	El equilibio para GGUF con casi cero ruido.
40+	Estándar	Máximo refinamiento de texturas complejas.

3. 🌫️ Comparativa de Denoise (Solo para i2i / Hires Fix)

0.35 - 0.45: Mantiene la estructura original pero con limpieza de artefactos.
0.50 - 0.65: El rango ideal para añadir detalle sin deformar el sujeto.
0.70+: Cambio significativo de composición (usar con precaución).

👤 Créditos y Atribución

Autor Original: Cyberdelia
Cuantización Experta: void-gryph

🚀 Despliegue en ComfyUI

Archivo GGUF: Mover a ComfyUI/models/unet/
Nodos Requeridos: Es necesario tener instalado ComfyUI-GGUF.
Componentes Originales: Use el CLIP y VAE incluidos en este repo para máxima fidelidad (extraídos sin prefijos de contenedor).

📝 Nota del Autor Original

Use Whop to access early releases, private pages, and the Tinkerer Discord role in one place.

CyberRealistic is a flexible, easy-to-use photorealistic model built from nonstop testing, custom blends, and just the right amount of chaos. The backstory? It’s honestly a wild mashup of different checkpoints, but what really counts is what you get in the end: sharp, expressive, clean renders that just work.

It’s tuned for both textual inversion and LoRA, so it’s great for anyone from total beginners to hardcore prompt wizards. If you’re making portraits, messing around with new styles, or just want a model that steps aside and does its job, CyberRealistic won’t let you down.

⚙️ Suggested Settings

Sampling method: DPM++ SDE Karras / DPM++ 2M Karras
VAE: is already Baked In Sampling steps: 30 Steps Resolution: 512x768 CFG: 5 Upscale: 2x Upscaler: 4x_NickelbackFS_72000_G Denoising strength: 0.3

🧠 Prompting

Negative prompt examples

lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry

💾 Backup & Resources backup location: huggingface

☕ Support the Project If this model helped you hit your vision faster, cleaner, or just plain better — consider [buying me a coffee]. It keeps the updates coming and the experiments wild.

💡 Need Better Prompts? This custom ChatGPT was made to top-tier prompts just for this model: 🔗 [Try it now on ChatGPT]

⚠️ Friendly Warning This model can generate mature content. Use responsibly. Respect laws, platforms, and people.

GGUF Quantizer - Comprimiendo la inteligencia artificial, píxel a píxel.

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GGUF

Model size

0.9B params

Architecture

sd1

Hardware compatibility

4-bit

5-bit

8-bit

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