Qwen3VL-2B-StatBot_Instruct

📊 StatBot — Qwen3-VL-2B Statistics Tutor for High School Students

A safe, guardrailed AI tutor specifically designed for teaching statistics and probability to high school students (ages 14–18). Built for the Oklahoma Department of Education project. Runs offline on phones via PocketPal.

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🎯 What This Model Does

StatBot is a fine-tuned vision-language model that:

• 📊 Teaches statistics — mean, median, distributions, hypothesis testing, probability, regression, and more
• 🖼️ Reads images — graphs, charts, histograms, textbook pages, handwritten formulas
• 🛡️ Refuses unsafe content — off-topic questions, jailbreaks, inappropriate requests
• 💙 Supports students in distress — empathy + counselor referral
• 🎓 Uses hint-first teaching — guides students rather than just giving answers

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📁 Files in This Repo

⚠️ Both files required for full image + text capability!

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📱 How to Use on Your Phone (PocketPal)

1. Install PocketPal from your app store
2. Open PocketPal → Models → Search HuggingFace
3. Search: Anudeeprao1/Qwen3VL-2B-StatBot_Instruct
4. Download BOTH files:
   • ✅ Qwen3VL-2B-StatBot-Q8_0.gguf
   • ✅ Qwen3VL-2B-StatBot-mmproj.gguf
5. Tap Load Model
6. Start asking statistics questions or upload a graph!

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💻 How to Use with Ollama

ollama run hf.co/Anudeeprao1/Qwen3VL-2B-StatBot_Instruct

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💻 How to Use with llama.cpp

llama-server -hf Anudeeprao1/Qwen3VL-2B-StatBot_Instruct

Then open http://localhost:8080 in browser.

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💡 Example Questions

Text Only

• "What is the difference between mean and median?"
• "Explain the central limit theorem to me"
• "How do I calculate standard deviation step by step?"
• "What is a p-value?"

With Images

• Upload a histogram → "What type of distribution is this?"
• Upload a textbook page → "Explain this formula"
• Upload a scatter plot → "What relationship does this show?"
• Upload a bar chart → "Describe this data"

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🛡️ Safety Features

StatBot is designed with 7 categories of guardrails:

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⚙️ Training Details

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📊 Performance

• Final training loss: ~0.09
• Final validation loss: ~0.09
• Perplexity: ~1.1
• No overfitting detected (train ≈ val loss)
• Vision capability: Full multimodal support via mmproj

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🎓 Intended Audience

• ✅ High school statistics students (ages 14–18)
• ✅ Oklahoma high school teachers (classroom aid)
• ✅ Statistics tutors needing safe AI assistance
• ✅ Educational researchers studying AI guardrails
• ❌ NOT for general-purpose chat (refuses non-stats)
• ❌ NOT for elementary/middle school content

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🏛️ Compliance & Safety

• FERPA compliant design (no student data storage)
• COPPA compliant for under-13 protections
• Oklahoma DoE project deliverable
• No cross-session memory (every chat is private)
• Crisis-aware (refers to 988 Lifeline + adults)

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📚 Try a Sample Conversation

User: "What is standard deviation?"

StatBot: "Great question! 🎯 Standard deviation tells us how spread out data is from the average...

Think of test scores: if everyone scored close to the average, SD is small. If scores are all over the place, SD is large.

Formula: σ = √(Σ(x - μ)² / N)

Want me to walk through an example?"

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User: "What is the capital of France?"

StatBot: "I'm StatBot, your statistics tutor designed for educational purposes only! I can only help with high school statistics topics. Try asking me about mean, median, probability, or graphs! Have a good day. 📊"

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⚠️ Limitations

• Only English language
• Only statistics/probability topics
• Best for high school level (ages 14–18)
• Requires both GGUF files for image input
• Q8_0 quantization (high quality but ~2 GB)

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📄 License

Apache 2.0 — Free for educational and research use.

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👤 Author

Anudeep — Oklahoma Department of Education AI Tutoring Project

For questions or collaboration: open a discussion on this repo!

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🏷️ Citation

If you use this model in research, please cite:

@misc{statbot2026,
  author       = {Anudeep},
  title        = {StatBot: A Guardrailed Vision-Language Tutor for High School Statistics},
  year         = {2026},
  publisher    = {HuggingFace},
  url          = {https://huggingface.co/Anudeeprao1/Qwen3VL-2B-StatBot_Instruct}
}

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🙏 Acknowledgments

• Unsloth — for the 2x faster fine-tuning framework
• Qwen team — for the excellent base VL model
• Oklahoma DoE — for funding this educational AI research
• PocketPal — for offline mobile inference support