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qassim-university/qu-llm-assistant
qu-llm-assistant is a text generation model from qassim-university. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
A fine-tuned Qwen2.5-1.5B-Instruct model specialised in answering student advisory questions for Qassim University (جامعة القصيم). The model is distributed as a Q4\K\M GGUF file for efficient local inference with llam…
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.gguf986 MB · 100%
From the Hugging Face model README
A fine-tuned Qwen2.5-1.5B-Instruct model specialised in answering student advisory questions for Qassim University (جامعة القصيم). The model is distributed as a Q4_K_M GGUF file for efficient local inference with llama.cpp / Ollama.
| Property | Value |
|---|---|
| Base model | Qwen/Qwen2.5-1.5B-Instruct |
| Fine-tuning method | LoRA (MLX framework) |
| Quantisation | Q4_K_M (GGUF) |
| File size | ~940 MB |
| Language | Arabic-primary, English-secondary |
| License | Apache-2.0 |
| Domain | University student advisory (academic rules, registration, scholarships, etc.) |
ollama run wesamhamad/qu-llm-assistant
Or pull the GGUF manually and create a local Modelfile:
FROM ./qassim-gpt-q4_k_m.gguf
SYSTEM "أنت مساعد ذكاء اصطناعي متخصص في الإجابة على استفسارات طلاب جامعة القصيم."
ollama create qu-llm-assistant -f Modelfile
ollama run qu-llm-assistant
llama-cli -m qassim-gpt-q4_k_m.gguf \
--chat-template qwen \
-p "ما هي متطلبات التسجيل في الفصل الدراسي الأول؟"
from llama_cpp import Llama
llm = Llama(model_path="qassim-gpt-q4_k_m.gguf", chat_format="qwen")
response = llm.create_chat_completion(messages=[
{"role": "system", "content": "أنت مساعد أكاديمي لجامعة القصيم."},
{"role": "user", "content": "كيف أتقدم لطلب إعادة تقييم الدرجات؟"},
])
print(response["choices"][0]["message"]["content"])
@misc{qu-llm-assistant-2025,
author = {Wesam Hamad},
title = {QU-LLM Assistant: Fine-tuned Qwen2.5-1.5B for Qassim University Advisory},
year = {2025},
publisher = {HuggingFace},
url = {https://huggingface.co/wesam3/qu-llm-assistant}
}
Apache-2.0 — see LICENSE.