Instructions to use tokenaii/Horus-1.0-4B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tokenaii/Horus-1.0-4B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="tokenaii/Horus-1.0-4B-GGUF",
	filename="Horus-1.0-4B-F16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use tokenaii/Horus-1.0-4B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf tokenaii/Horus-1.0-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf tokenaii/Horus-1.0-4B-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 tokenaii/Horus-1.0-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf tokenaii/Horus-1.0-4B-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 tokenaii/Horus-1.0-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf tokenaii/Horus-1.0-4B-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 tokenaii/Horus-1.0-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf tokenaii/Horus-1.0-4B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/tokenaii/Horus-1.0-4B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use tokenaii/Horus-1.0-4B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tokenaii/Horus-1.0-4B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tokenaii/Horus-1.0-4B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tokenaii/Horus-1.0-4B-GGUF:Q4_K_M

Ollama
How to use tokenaii/Horus-1.0-4B-GGUF with Ollama:
```
ollama run hf.co/tokenaii/Horus-1.0-4B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use tokenaii/Horus-1.0-4B-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 tokenaii/Horus-1.0-4B-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 tokenaii/Horus-1.0-4B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for tokenaii/Horus-1.0-4B-GGUF to start chatting

Docker Model Runner
How to use tokenaii/Horus-1.0-4B-GGUF with Docker Model Runner:
```
docker model run hf.co/tokenaii/Horus-1.0-4B-GGUF:Q4_K_M
```

Lemonade

How to use tokenaii/Horus-1.0-4B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull tokenaii/Horus-1.0-4B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Horus-1.0-4B-GGUF-Q4_K_M

List all available models

lemonade list

Hours-1.0-4B-GGUF

GGUF quantized versions of Horus-1.0-4B by TokenAI.

Base Model

Source: tokenaii/horus
Original Model: Horus-1.0-4B (4B parameters)
Developer: Assem Sabry & TokenAI
Organization: TokenAI
Release Date: April 2026
License: MIT

About TokenAI

TokenAI is an AI startup founded by Assem Sabry with headquarters in Egypt.

Mission

TokenAI aims to deliver the strongest language models in the world and in the Arab world through the Horus family of models. The startup bridges the gap between cutting-edge AI capabilities and regional cultural contexts, starting with the Arab world.

The Horus Family

Horus-1.0-4B marks the first model in the Horus family line. This is just the beginning of TokenAI's journey to create a comprehensive suite of AI models serving the Arab region.

Horus-1.0-4B-GGUF

GGUF quantized versions of Horus-1.0-4B - A 4B parameter multilingual language model optimized for Arabic and English.

Model Variants & Hardware Requirements

Format	File Size	Min RAM (CPU)	Min VRAM (GPU)	Quality	Best For
F16	9.03 GB	12 GB	10 GB	Maximum quality	High-end GPUs (RTX 3090, A100)
Q8_0	4.8 GB	6 GB	5 GB	Near-lossless	RTX 3060 12GB, RTX 4060
Q6_K	3.71 GB	5 GB	4 GB	Excellent	RTX 3060, RTX 4060 Laptop
Q5_K_M	3.23 GB	4 GB	3.5 GB	Very Good	GTX 1650, RTX 3050
Q4_K_M	2.78 GB	3.5 GB	3 GB	Good	Entry-level GPUs, CPU-only

Detailed Hardware Requirements

F16 (FP16 - Full Precision)

File: Horus-1.0-4B-F16.gguf (9.03 GB)
Min System RAM: 12 GB
Min VRAM: 10 GB
Recommended: RTX 3090, RTX 4090, A100, A6000
Use Case: Maximum quality, research, fine-tuning reference

Q8_0 (8-bit Quantization)

File: Horus-1.0-4B-Q8_0.gguf (4.8 GB)
Min System RAM: 6 GB
Min VRAM: 5 GB
Recommended: RTX 3060 12GB, RTX 4060, RTX 4070
Use Case: Near-lossless quality with half the memory

Q6_K (6-bit K-Quant)

File: Horus-1.0-4B-Q6_K.gguf (3.71 GB)
Min System RAM: 5 GB
Min VRAM: 4 GB
Recommended: RTX 3060, RTX 4060 Laptop, GTX 1080 Ti
Use Case: Excellent quality for most applications

Q5_K_M (5-bit K-Quant Medium)

File: Horus-1.0-4B-Q5_K_M.gguf (3.23 GB)
Min System RAM: 4 GB
Min VRAM: 3.5 GB
Recommended: GTX 1650 Super, RTX 3050, RTX 3050 Ti
Use Case: Balanced quality and performance

Q4_K_M (4-bit K-Quant Medium)

File: Horus-1.0-4B-Q4_K_M.gguf (2.78 GB)
Min System RAM: 3.5 GB
Min VRAM: 3 GB
Recommended: GTX 1060 6GB, GTX 1650, Intel Arc A380
Use Case: Maximum compression, edge devices, CPU inference

Quick Start

Using NeuralNode (Recommended)

The easiest way to use Horus GGUF models is with the NeuralNode framework:

import neuralnode as nn

MODEL_ID = "tokenaii/Hours-1.0-4B-GGUF/Horus-1.0-4B-Q6_K.gguf"
DEVICE = "cpu"  # Change to "cuda" for GPU acceleration

# Download and load
model = nn.HorusModel(MODEL_ID, device=DEVICE).load()

# Use immediately
response = model.chat([{"role": "user", "content": "hi horus im emy"}])
print(response.content)

Using llama-cpp-python

For direct llama.cpp integration:

from llama_cpp import Llama

llm = Llama(
    model_path="Horus-1.0-4B-Q4_K_M.gguf",
    n_ctx=4096
)

output = llm("Hello, how are you?", max_tokens=256)
print(output['choices'][0]['text'])

Voice Interface with Replica TTS

Add natural voice output to your Horus GGUF model with Replica TTS:

import neuralnode as nn

voice_id = "replica-aria-language{en-us}"

MODEL_ID = "tokenaii/Hours-1.0-4B-GGUF/Horus-1.0-4B-F16.gguf"
DEVICE = "cuda"

# Load model with Replica TTS
model = nn.HorusModel(
    MODEL_ID,
    tts_engine="replica_tts",
    voice=voice_id,
    device=DEVICE
).load()

# Chat and get spoken response
response = model.chat([{"role": "user", "content": "Hello!"}])
print(response.content)
response.play_audio()  # Plays the TTS audio

Browse All Voices

import neuralnode as nn

voices = nn.replica_voice_list()
for voice in voices:
    print(voice)

Benchmark Results

Below are visual comparisons of Horus-1.0-4B against leading models.

General Knowledge & Reasoning

Arabic Language & Cultural Benchmarks

Coding & Tool Use Benchmarks

Model Capabilities

Multilingual: Supports 10+ languages including Arabic, English, French, Spanish, German, Italian, Portuguese, Turkish, Urdu, Hindi
Identity Recognition: Knows itself as Horus from TokenAI
Reasoning: Chain-of-thought capabilities
Context Length: Up to 4096 tokens
Voice Output: Replica TTS integration for natural speech

Model tree for tokenaii/Horus-1.0-4B-GGUF

Base model

tokenaii/horus

Quantized

(1)

this model

tokenaii
/

Horus-1.0-4B-GGUF