初始化项目，由ModelHub XC社区提供模型
Model: tokenaii/Horus-1.0-4B-GGUF Source: Original Platform
This commit is contained in:
ModelHub XC
222
README.md
Normal file
222
README.md
Normal file
@@ -0,0 +1,222 @@
|
||||
---
|
||||
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
|
||||
|
||||
|
||||
|
||||
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
|
||||
|
||||
|
||||
### 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
|
||||
|
||||
---
|
||||
|
||||
## 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.
|
||||
Reference in New Issue
Block a user