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BLACK0X80
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Model Details
Model Provider
BLACK0X80
Model Tree
meta-llama/Llama-3.1-8B
Input Modalities
Output Modalities
Supported Functionality
horus-egy-coder is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct trained to assist Arabic-speaking developers — with native understanding of Egyptian Arabic technical dialect. It can explain code in Arabic, help debug in conversational Egyptian, and write clean code with Arabic comments.
| Property | Value |
|---|---|
| Base model | meta-llama/Llama-3.1-8B-Instruct |
| Parameters | 1B (quantized BF16) |
| Training | Unsloth + HuggingFace TRL (2x faster) |
| License | Apache 2.0 |
| Language | Arabic 🇪🇬 / English |
| Task | Code generation, explanation, debugging |
python
from transformers import AutoTokenizer, AutoModelForCausalLMimport torch model_name = "BLACK0X80/horus-egy-coder" tokenizer = AutoTokenizer.from_pretrained(model_name)model = AutoModelForCausalLM.from_pretrained( model_name, torch_dtype=torch.bfloat16, device_map="auto") messages = [ { "role": "system", "content": "أنت مساعد برمجة بيتكلم عربي مصري. بتشرح الكود بالعربي وبتساعد المطورين." }, { "role": "user", "content": "اكتبلي function بـ Python بتحسب الـ factorial" }] input_ids = tokenizer.apply_chat_template( messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to(model.device) output = model.generate( input_ids, max_new_tokens=512, temperature=0.7, do_sample=True) print(tokenizer.decode(output[0][input_ids.shape[1]:], skip_special_tokens=True))Example 1 — Code explanation in Arabic:
text
User: فسرلي الكود ده for i in range(len(arr)-1): for j in range(len(arr)-i-1): if arr[j] > arr[j+1]: arr[j], arr[j+1] = arr[j+1], arr[j] Model: ده Bubble Sort — خوارزمية ترتيب بسيطة. بتعمل loop على الـ array وبتقارن كل عنصر بالي بعده، لو العنصر الأكبر جه الأول بتبدلهم...Example 2 — Debugging:
text
User: الكود ده بيطلع IndexError، مش عارف ليهModel: المشكلة في السطر ده... جرب كذا...🔢 GGUF Version (للأجهزة المحدودة)
لو جهازك مش عنده GPU كبير، استخدم النسخة المضغوطة:
BLACK0X80/horus-egy-coder-Q4_K_M-GGUF
bash
# تشغيل بـ llama.cpp./llama-cli -m horus-egy-coder-Q4_K_M.gguf \ -p "أنت مساعد برمجة عربي مصري." \ --chat-format llama-3unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bitGood for:
Limitations:
HORUS-AI is an Egyptian AI initiative focused on building Arabic and Egyptian-dialect AI models. Named after the ancient Egyptian god of knowledge, we aim to make AI accessible to Arabic-speaking developers.
bibtex
@misc{horus-egy-coder-2025, title={Horus-Egy-Coder: Egyptian Arabic Coding Assistant}, author={BLACK0X80 and HORUS-AI}, year={2025}, url={https://huggingface.co/BLACK0X80/horus-egy-coder}, note={Fine-tuned from meta-llama/Llama-3.1-8B-Instruct}}Made with ❤️ in Egypt 🇪🇬
from transformers import AutoTokenizer, AutoModelForCausalLMimport torch model_name = "BLACK0X80/horus-egy-coder" tokenizer = AutoTokenizer.from_pretrained(model_name)model = AutoModelForCausalLM.from_pretrained( model_name, torch_dtype=torch.bfloat16, device_map="auto") messages = [ { "role": "system", "content": "أنت مساعد برمجة بيتكلم عربي مصري. بتشرح الكود بالعربي وبتساعد المطورين." }, { "role": "user", "content": "اكتبلي function بـ Python بتحسب الـ factorial" }] input_ids = tokenizer.apply_chat_template( messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to(model.device) output = model.generate( input_ids, max_new_tokens=512, temperature=0.7, do_sample=True) print(tokenizer.decode(output[0][input_ids.shape[1]:], skip_special_tokens=True))User: فسرلي الكود ده for i in range(len(arr)-1): for j in range(len(arr)-i-1): if arr[j] > arr[j+1]: arr[j], arr[j+1] = arr[j+1], arr[j]Model: ده Bubble Sort — خوارزمية ترتيب بسيطة. بتعمل loop على الـ array وبتقارن كل عنصر بالي بعده، لو العنصر الأكبر جه الأول بتبدلهم...# تشغيل بـ llama.cpp./llama-cli -m horus-egy-coder-Q4_K_M.gguf \ -p "أنت مساعد برمجة عربي مصري." \ --chat-format llama-3@misc{horus-egy-coder-2025, title={Horus-Egy-Coder: Egyptian Arabic Coding Assistant}, author={BLACK0X80 and HORUS-AI}, year={2025}, url={https://huggingface.co/BLACK0X80/horus-egy-coder}, note={Fine-tuned from meta-llama/Llama-3.1-8B-Instruct}}