README.md

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title: README
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  <img src="assets/aifoundry-banner.png" alt="AI Foundry CORE-ET Hackathon" width="100%">
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# 🚀 Welcome to the AIFoundry CORE-ET Hackathon

Port real models. Run them on real silicon. Share the results. ⚡

This is a community hackathon for people who want to make open AI workloads run
closer to the edge: vision, speech, audio, local language models, robotics,
drones, and weird benchmark ideas that deserve to touch hardware. 🤗

## 🏁 Ready to join?

First step: join the Hugging Face organization so you show up with the rest of
the teams, follow shared resources, and get the latest hackathon updates.

### 👉 [Join the AIFoundry Hackathon Org](https://huggingface.co/organizations/AIFoundry-hackathon/share/lFEBkpoCildVMScJWZeSpPDGfmpCpOYRHc)

Bring your teammates too. The org page is the public roster for people, teams,
models, demos, and board results around the hackathon. 🌍

## 🧩 Pick a quest

| Quest | What you can build |
|-------|---------------------|
| 👁️ Vision | Denoising, detection, camera-first edge workloads |
| 🎙️ Speech + audio | Whisper-style kernels and streaming-friendly pipelines |
| 🧠 Local LLMs | GGUF and `llama.cpp` flows on ET-backed runtimes |
| 🤖 Robotics + drones | Perception, control, and low-power deployment paths |
| ⚙️ Systems | Faster kernels, better memory movement, cleaner board runners |
| 🧪 Wildcard | Bring your own open model and make the benchmark reproducible |

## 📦 Model repo

The model repo is the technical home for examples, docs, benchmark artifacts,
and the submission path:

### 👉 [Open the CORE-ET model repo](https://huggingface.co/AIFoundry-hackathon/hf-hackathon)

Start from an existing port, improve a kernel, add a new model, or package a
small demo that shows why your port matters.

## 🧭 How participation works

1. 🤝 Join this Hugging Face organization.
2. 👯 Team up or go solo.
3. 🎯 Pick a model, kernel, benchmark, or demo target.
4. 📚 Use the model repo to follow the technical path.
5. 🚀 Submit your port or improvement.
6. 📊 The board workflow runs and comments back with results.

## 🌱 Good first contributions

- ⚡ Improve an existing DnCNN, YOLO, Whisper, or LLM benchmark.
- 📌 Add a new open model with a pinned Hugging Face reference.
- 🏁 Make a kernel faster and document the board result.
- 🎬 Package a small demo that shows the workload in action.
- 🫶 Help another participant reproduce a run.

## 💬 Need help?

Join Discord and ask in `#community-lab`:

<https://discord.gg/CbSA2umxf6>

Tell us what you want to port, what hardware access you need, and whether you
are looking for teammates.