Real-time communication layer for remote SLEAP training and inference
Project description
sleap-rtc
sleap-rtc lets you run SLEAP training and inference on a remote GPU from your local machine.
Installation
On the worker (GPU machine):
uv tool install --python 3.11 sleap-rtc --with "sleap-nn[torch]" --with-executables-from sleap-nn --torch-backend auto
Setup
1. Get an API key and create a room
Go to the sleap-rtc dashboard, log in with GitHub, and:
- Generate an API key under Tokens
- Create a room under Rooms and note the room secret
2. Start the worker
sleap-rtc login --api-key <api-key>
sleap-rtc config add-mount /path/to/your/data
sleap-rtc worker --room-secret <secret>
3. Submit a job
Open SLEAP, go to the Remote Training dialog, paste the session string displayed by the worker, and submit.
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