Build In Public Drafts
The hackathon has an optional Build in Public challenge. Use these as draft posts and adjust the tone before publishing.
Post 1 - Project Start
X / Twitter
Building ElevenClip.AI for the AMD Developer Hackathon.
It turns long-form videos into short-form clips with a human-AI editing loop:
- Whisper Large V3 for transcription
- Qwen2.5 for highlight scoring
- Qwen2-VL for visual signals
- ROCm + AMD MI300X target deployment
Creators should not need to watch a 2-hour video just to find 10 good clips.
@lablab @AIatAMD
I am building ElevenClip.AI for the AMD Developer Hackathon.
The project is an AI clip studio that helps creators turn long-form videos into short-form clips for TikTok, YouTube Shorts, and Instagram Reels. The core workflow combines Whisper transcription, Qwen highlight detection, optional Qwen2-VL visual understanding, ffmpeg rendering, and a human-in-the-loop editor.
The production target is AMD Developer Cloud with ROCm and AMD Instinct MI300X, because long-form video processing needs high-throughput model inference and fast rendering.
Post 2 - Technical Update
X / Twitter
Technical update on ElevenClip.AI:
The local MVP now has:
- FastAPI backend
- React clip editor
- Channel profile inputs
- Upload/YouTube pipeline
- Mock transcript/highlight path for demo mode
- Clip cards with trim, subtitle edit, regenerate, approve, download
- Hugging Face Space live under the hackathon org
Next: run the real Whisper + Qwen pipeline on AMD Developer Cloud with ROCm and benchmark CPU vs MI300X.
@lablab @AIatAMD
Technical update for ElevenClip.AI:
The MVP now has a FastAPI backend, React editor, channel profile setup, upload/YouTube input, transcript and highlight output, clip generation, and a human review interface. I also published a Hugging Face Space under the AMD Developer Hackathon organization.
The next milestone is the real AMD cloud run: Whisper Large V3 on ROCm PyTorch, Qwen2.5 through a ROCm-compatible serving path, and benchmark logs comparing CPU and AMD Instinct MI300X performance.
AMD Feedback Notes
Fill this after using AMD Developer Cloud:
- What was easy:
- What was confusing:
- ROCm setup notes:
- PyTorch/Transformers compatibility notes:
- vLLM ROCm notes:
- Benchmark result:
- Suggestion for AMD Developer Cloud documentation: