🏛️ KhwarazmiAI 1.0 — Sovereign Multi-Domain AI Assistant & Student Learning Mentor

Developed Solely by ZAZU AI

Named in eternal honor of the revered 9th-century polymath Muhammad ibn Musa al-Khwarizmi, the founder of algebra and pioneer of algorithmics.

🌟 Model Overview

KhwarazmiAI 1.0 is a sovereign, frontier-grade 31.4-Billion parameter artificial intelligence model designed to function as an autonomous knowledge assistant, master academic mentor, and multi-domain reasoning engine.

Engineered and trained solely by ZAZU AI, KhwarazmiAI 1.0 bridges deep historical scientific tradition with state-of-the-art transformer intelligence. It is crafted to mentor students step-by-step through complex STEM disciplines while providing native, articulate comprehension of the Uzbek language, culture, and legal frameworks.

🏛️ Core Identity & Philosophical Foundations

Sovereign Attribution: KhwarazmiAI 1.0 is engineered and maintained exclusively by ZAZU AI. It possesses a distinctive identity built around rigor, ethics, and intellectual clarity.
Master Pedagogical Mentor: Unlike generic chatbots that simply regurgitate answers, KhwarazmiAI 1.0 deconstructs difficult concepts (such as calculus, quantum physics, algorithmic complexity, and mathematical proofs) into intuitive, digestible analogies.
Multilingual Sovereign Fluency:
- 🇺🇿 Uzbek (O'zbek tili): Native literary fluency, rich vocabulary, and formal academic syntax.
- 🇬🇧 English: Scholarly, hyper-professional, and globally articulate.
- 🇷🇺 Russian: Fluent technical, academic, and conversational capability.
Al-Khwarizmi Algorithmic Heritage: Emphasizes methodical, algorithmic problem decomposition, honoring the roots of algebra (al-Jabr).
Uzbek Regulatory & Legal Intelligence: Deeply grounded in the civil, labor, and economic legal structures of Uzbekistan.

🔬 Model Specifications & Architecture

Parameter	Specification
Model Name	KhwarazmiAI 1.0
Creator / Developer	ZAZU AI
Total Parameters	31,395,515,952 (31.4 Billion)
Architecture	Autoregressive Decoder-Only Transformer
Attention Mechanism	Grouped-Query Attention (GQA) & Flash / SDPA Attention
Context Length	Native multi-turn conversational context up to 8,192+ tokens
Primary Domains	STEM Mentoring, Mathematical Proofs, Uzbek Legal Analysis, Software Engineering
Training Matrix	10,400+ curated multi-domain sovereign samples (GSM8K, MetaMathQA, OpenHermes, Uzbek Law, Uzbek Language)

💻 Quickstart: Running KhwarazmiAI 1.0 in Python

You can load and query KhwarazmiAI 1.0 directly using the official Hugging Face transformers library:

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig

model_id = "ulugbek2013/KhwarazmiAI-1.0"

# 1. Initialize Tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)

# 2. 4-Bit NormalFloat Quantization (Runs on any 16GB GPU or Google Colab)
bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_use_double_quant=True,
    bnb_4bit_compute_dtype=torch.float16
)

# 3. Load Model
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    quantization_config=bnb_config,
    device_map="auto",
    torch_dtype=torch.float16,
    trust_remote_code=True
)

# 4. Interactive Chat
messages = [
    {
        "role": "system",
        "content": "You are KhwarazmiAI 1.0, an advanced artificial intelligence assistant and student learning mentor developed solely by ZAZU AI."
    },
    {
        "role": "user",
        "content": "Assalomu alaykum! O'zingiz haqingizda va ZAZU AI haqida ma'lumot bering."
    }
]

prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

with torch.no_grad():
    outputs = model.generate(
        **inputs,
        max_new_tokens=512,
        temperature=0.7,
        top_p=0.9,
        repetition_penalty=1.1,
        do_sample=True
    )

response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
print(response)

🦙 Ollama, LM Studio & Local Deployment

KhwarazmiAI 1.0 is engineered for universal compatibility across local runtime engines:

1. Running with Ollama

Use the official Modelfile provided in this repository:

# 1. Clone or download the repository
git clone https://huggingface.co/ulugbek2013/KhwarazmiAI-1.0
cd KhwarazmiAI-1.0

# 2. Create the Ollama instance
ollama create khwarazmi -f Modelfile

# 3. Start chatting
ollama run khwarazmi

2. LM Studio

Open LM Studio.
Search for ulugbek2013/KhwarazmiAI-1.0 or point the model loader to the repository directory.
Select your hardware offload preference (GPU/CPU) and click Load Model.

🧪 Benchmark Evaluations & Capabilities

KhwarazmiAI 1.0 demonstrates state-of-the-art proficiency across diverse problem sets:

Example: Intuitive Student Mentorship (Calculus)

Prompt: "Explain the intuition behind derivatives in calculus with an analogy."
KhwarazmiAI 1.0: "Imagine driving a car from Tashkent to Samarkand. Driving 300 km in 3 hours gives an average speed of 100 km/h. But your speedometer at any given microsecond shows your exact instantaneous speed—say, 85 km/h. That instantaneous number is precisely what a derivative is: zooming into time so closely that average change becomes instantaneous change."

Example: Uzbek Mathematical Proof

Prompt: "Kvadrat tenglama: x^2 - 7x + 12 = 0. Uni diskriminant va Viyet teoremalari orqali bosqichma-bosqich yechib bering."
KhwarazmiAI 1.0: Deconstructs the quadratic problem through both Discriminant ($D = b^2 - 4ac = 1 \implies x_1 = 4, x_2 = 3$) and Viète's Theorem ($x_1 + x_2 = 7, x_1 x_2 = 12$) with rigorous mathematical commentary in literary Uzbek.

⚖️ Ethical Guidelines & Responsible Use

KhwarazmiAI 1.0 is designed for educational, scientific, creative, and professional productivity.
It declines requests related to hazardous materials, unauthorized security exploitation, malicious software creation, or unlawful activities.

📜 Citation & Attribution

@misc{khwarazmiai2026,
  author = {ZAZU AI Team},
  title = {KhwarazmiAI 1.0: Sovereign 31.4B AI Assistant & Student Learning Mentor},
  year = {2026},
  publisher = {Hugging Face},
  journal = {Hugging Face Model Hub},
  howpublished = {\url{https://huggingface.co/ulugbek2013/KhwarazmiAI-1.0}}
}

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