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Model: tokenaii/Horus-1.0-4B-GGUF Source: Original Platform
2026-04-22 02:44:41 +08:00
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+---
+license: mit
+language:
+- ar
+- en
+- fr
+- es
+- de
+- it
+- pt
+- tr
+- ur
+- hi
+tags:
+- llama
+- llm
+- text-generation
+- multilingual
+- causal-lm
+- arabic
+- gguf
+- quantized
+- horus
+- tokenai
+- neuralnode
+- tts
+- voice
+base_model: tokenaii/horus
+widget:
+  - text: "### User:\nWhat is the capital of Egypt?\n\n### Assistant:\nThe capital of Egypt is Cairo."
+  - text: "### User:\nمن هو أول رئيس لمصر؟\n\n### Assistant:\nأول رئيس لمصر بعد ثورة 1952 هو محمد نجيب."
+  - text: "### User:\nHello Horus!\n\n### Assistant:\nHello! I'm Horus, an AI assistant developed by TokenAI. How can I help you today?"
+inference: true
+---
+
+# Hours-1.0-4B-GGUF
+
+![Horus Model](media/main.png)
+
+GGUF quantized versions of Horus-1.0-4B by TokenAI.
+
+## Base Model
+
+- **Source:** [tokenaii/horus](https://huggingface.co/tokenaii/horus)
+- **Original Model:** Horus-1.0-4B (4B parameters)
+- **Developer:** [Assem Sabry](https://assem.cloud/) & TokenAI
+- **Organization:** [TokenAI](https://tokenai.cloud/)
+- **Release Date:** April 2026
+- **License:** MIT
+
+## About TokenAI
+
+**TokenAI** is an AI startup founded by [Assem Sabry](https://assem.cloud/) 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:
+
+```python
+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:
+
+```python
+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:
+
+```python
+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
+
+```python
+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
+![General Benchmarks](media/1.png)
+
+### Arabic Language & Cultural Benchmarks
+![Arabic Benchmarks](media/2.png)
+
+### Coding & Tool Use Benchmarks
+![Coding Benchmarks](media/3.png)
+
+---
+
+## 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
+
+---
+
+## Links
+
+- **Base Model:** https://huggingface.co/tokenaii/horus
+- **TokenAI Website:** https://tokenai.cloud/
+- **Developer:** https://assem.cloud/
+- **GitHub:** https://github.com/tokenaii/horus-1.0
+
+---
+
+**Note:** Quantized using llama.cpp for efficient inference. GGUF versions are optimized for local deployment with minimal resource requirements.
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