HACKATHON-CONTEXT.md

Build Small Hackathon — Full Context (Hugging Face × Gradio)

Verified from the official field guide + live org scan. Shared reference for this project. No deadlines/timelines recorded here by design — sequence work by dependency, not calendar.

The premise

A return to small, local, tinkerable open-weight models — everything under 32B parameters, running on hardware you own. "Less API bill, more workshop."

Two tracks (equal prize pools, pick one per app)

• 🏡 Backyard AI (practical): "Practical, problem-solving apps built to improve daily life — for you or someone close to you. Useful things that run on hardware you own." (storybook generator, study tutor, receipt/bill parser, on-device doc assistant)
• 🍄 An Adventure in Thousand Token Wood (whimsical): "Whimsical, delightful, AI-native apps that push the boundaries of fun." AI must be load-bearing, not a build helper. (interactive games, entertainment tools, desktop pet, text-adventure DM)

Entry criteria

• REQ-01 — Under 32B: every model your project depends on must be <32B total params (not just active). Combine several freely; each must individually stay under the cap.
• REQ-02 — Ship a Gradio app in the official build-small-hackathon HF org (Docker fine if the interface is a Gradio Space).
• REQ-03 — Record a demo video showing the app working (judges fall back to it if GPU/API limits block a live run — treat it as the primary judged artifact).
• REQ-04 — Post on social, link it from the README.
• REQ-05 — GPU limit: submit as many apps as you like; if relying on free ZeroGPU, max 10 ZeroGPU apps/user (Modal credits or consumer HW otherwise).
• REQ-06 — Tag your README frontmatter for the tracks + badges you want considered, plus a short write-up of the idea & tech. (No single canonical tag spelling is enforced; the wild uses several variants — include both hyphen and space forms.)

Prize table — $48k cash + 20k Modal credits + 2× RTX 5080 + ChatGPT Pro (29 ways to win)

General track prizes — awarded PER TRACK (Backyard and Wood each):

Place	Prize
1st	$4,000
2nd	$2,500
3rd	$1,500
4th	$1,000
Community Choice (by likes)	$2,000

Sponsor prizes (own criteria):

• ⚙️ Best Use of Modal — 1st 10,000 / 2nd 7,000 / 3rd 3,000 CREDITS ($20k total). "Use Modal for the development or runtime of your app, and note it in your Space README. Judged on best use of the platform. Inference, fine-tuning, batch jobs and sandboxes all count."
• 🧠 Best MiniCPM Build (OpenBMB) — $2,500 / $1,500 / $1,000 PER TRACK ($5k per track, $10k total). Build with MiniCPM models; Vision (MiniCPM-V) & omni (MiniCPM-o) variants qualify.
• 💻 Best Use of Codex (OpenAI) — $5,000 / $3,000 / $1,000 ($10k). Requires Codex-attributed commits in the connected repo/Space.
• 🟩 Nemotron Hardware Prize (NVIDIA) — 2× RTX 5080: one "best space" (NVIDIA-judged on merit), one "community engagement" (likes). Build with Nemotron models.

Bonus badges:

• Off Brand $1,500 — best custom UI beyond default Gradio ("gr.Server is your friend").
• Tiny Titan $1,500 — best app on a genuinely tiny model; ALL models ≤4B.
• Best Demo $1,000 — best full package: app + demo video + social post.
• Best Agent $1,000 — best agentic app (multi-step tool use + planning, <32B).
• Bonus Quest Champion $2,000 — most bonus criteria met across the board.
• Judges' Wildcard $1,000 — amazing but fits no category (every submission auto-entered; no action).

Rules that matter

• Awards stack — one app can win a track placement + sponsor prizes + bonus badges simultaneously.
• Multiple submissions allowed, each judged independently.
• Sponsor models must form a core part of the experience (you may also use other providers' models under the cap).
• Some prizes require running locally to be eligible; hosted sponsor APIs exist for dev.

Sponsor models & platforms (verified)

• OpenBMB / MiniCPM (free hosted API + local via llama.cpp/transformers):
  • MiniCPM-V-4.6 (1.3B) — vision/OCR/document understanding. Class AutoModelForImageTextToText + AutoProcessor; transformers[torch]>=5.7 (+ av for video, avoids torchcodec/CUDA issues). Starter Space to fork: openbmb/MiniCPM-V-4.6-Demo (gr.Server).
  • MiniCPM-o-4_5 (9.4B) — full-duplex omni (voice/vision/language in, speech out). AutoModel + trust_remote_code; model.chat(msgs=..., use_tts_template=, enable_thinking=, generate_audio=) — content as a list, no tokenizer arg.
  • MiniCPM5-1B (1.08B, llama arch) — text gen, tool-calling, on-device. AutoModelForCausalLM.
  • MiniCPM4.1-8B — text reasoning.
  • VoxCPM2 (2B) — TTS, 48kHz, PyTorch ≥2.5.0. Voice Design (description)text (no ref); Controllable Cloning generate(text="(style)text", reference_wav_path=...); Ultimate Cloning adds prompt_wav_path+prompt_text. Style varies run-to-run (gen 1–3×).
• NVIDIA / Nemotron 3 family: Nano (30B MoE reasoning), Nano-4B (edge), Nano-Omni (multimodal), ASR (nemotron-speech-streaming-en-0.6b [kit-recommended] or nemotron-3.5-asr-streaming-0.6b [multilingual]), Parse (NVIDIA-Nemotron-Parse-v1.2, sub-1B doc extraction: tables/math/handwriting/figures/layout), Embed-VL.
• Modal (serverless GPU): inference, fine-tuning (hp_sweep_gpt: 8 SLMs in parallel; fine-tuning-embeddings; Ramp case study — parallel fine-tune, 79% cost cut), batch (spawn_map, 1M jobs/1 line, scale-to-zero), sandboxes (run untrusted/LLM-generated code — flagship pattern: examples/agent, safe_code_execution; the GRPO example notes the Best Use of Modal prize "showcased sandboxes for securely evaluating model-generated code"). Memory snapshots, Volumes, scheduled jobs.
• Black Forest Labs FLUX.2 Klein (4B/9B image); JetBrains Mellum 2 (12B MoE code); Cohere Transcribe (ASR) + Tiny Aya.

Submission process

Join the org → upload the Gradio Space → record a demo video (host on YouTube/Space/public) → one social post → update README with links + frontmatter tags + a short write-up. Submit when ready.

This portfolio's Modal strategy (context for both apps)

Two apps, both engineered to be 1st-caliber for Best Use of Modal, on different flagship axes so they don't cannibalize the single top slot:

• WitnessBox — Axis A: Sandbox runs model-generated code (the pattern Modal's prize "showcased").
• Tiny Foundry — Axis B: massive elastic parallel scale (dozens of GPU containers at once; Modal Batch's core identity). Goal: maximize P(winning 1st) + a real shot at a 1st + 2nd sweep. Awards stack, so each also pursues OpenBMB / Tiny Titan / Well-Tuned / track placements as secondary.