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A newer version of the Gradio SDK is available: 6.22.0

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metadata 
title: Plane Mode Scholar
emoji: ✈️
colorFrom: blue
colorTo: indigo
sdk: gradio
app_file: app.py
pinned: false
license: mit
short_description: Fine-tuned Nemotron 4B study coach + MemoryAgent
suggested_hardware: l4x1
startup_duration_timeout: 1h
models:
  - GuusBouwensNL/plane-mode-nemotron-4b-study-coach
  - nvidia/NVIDIA-Nemotron-3-Nano-4B-GGUF
preload_from_hub:
  - nvidia/NVIDIA-Nemotron-3-Nano-4B-GGUF NVIDIA-Nemotron3-Nano-4B-Q4_K_M.gguf
  - >-
    GuusBouwensNL/plane-mode-study-coach-lora-gguf
    plane-mode-study-coach-lora.gguf
tags:
  - Backyard AI
  - Off-Brand
  - Sharing is Caring
  - Field Notes
  - Best Agent
  - Off the Grid
  - Well-Tuned
  - track:backyard
  - sponsor:nvidia
  - achievement:offgrid
  - achievement:welltuned
  - achievement:offbrand
  - achievement:llama
  - achievement:sharing
  - achievement:fieldnotes

Plane Mode Scholar

Build Small Hackathon entry — Backyard AI track, Nemotron Quest.

I built this for a grad student who studies on planes and in libraries where Wi-Fi drops constantly. Most study apps forget everything between sessions. This one remembers what you got wrong, what exam is coming up, and how you like things explained.

Hit FLY once. The agent packs your materials, pulls up due reviews, explains a topic with citations from your notes, and runs a quiz. No tab-hopping.

The coach is a fine-tuned Nemotron 3 Nano 4B — SFT on real study conversations. UI is custom HTML on gr.Server, loosely based on my SwarmGrid project.

Demo

Plane Mode Scholar autopilot demo

One tap FLY, then watch it plan → retrieve → explain → quiz. Runs offline with llama.cpp if you need that.

Space https://huggingface.co/spaces/build-small-hackathon/plane-mode-scholar
Demo MP4 https://github.com/GJB99/plane-mode-scholar/raw/demo-v1/docs/demo/plane-mode-scholar-demo.mp4
Social post https://x.com/GuusBouwens/status/2066670913467400284
Field notes docs/field-notes.md
Badge writeup docs/badges.md
Trace dataset docs/agent-traces-dataset.jsonl

Badges

Badge What we did
Well-Tuned LoRA SFT on Nemotron 4B → plane-mode-nemotron-4b-study-coach
Off the Grid Local inference via llama.cpp GGUF — no cloud LLM calls
Off-Brand Custom dashboard, not default Gradio tabs
Llama Champion ./scripts/start_llamacpp.sh runs the fine-tune through llama-server
Sharing is Caring Open agent traces + /export_trace endpoint
Field Notes docs/field-notes.md — what broke, what surprised me
Best Agent StudyAgent does monitor → plan → act without user clicking through steps
Nemotron Quest Nemotron 3 Nano family throughout (4B coach, 30B MoE fallback)

Fine-tune details: docs/finetune.md. Colab notebook in notebooks/.

Try it locally 

pip install -r requirements.txt
export HF_TOKEN=your_token
python app.py

Open http://localhost:7860.

Fully offline path — download the GGUF, start llama-server with the LoRA, point the app at it:

./scripts/setup_llamacpp_stack.sh   # first time only
./scripts/start_llamacpp.sh           # terminal 1
PMS_INFERENCE_BACKEND=llamacpp python app.py   # terminal 2

Models

Role Model
Coach (default) GuusBouwensNL/plane-mode-nemotron-4b-study-coach
Base nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16
Heavy fallback nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8
Offline GGUF nvidia/NVIDIA-Nemotron-3-Nano-4B-GGUF
Embeddings sentence-transformers/all-MiniLM-L6-v2

Repo: github.com/GJB99/plane-mode-scholar

MIT