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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:

  1. Generate an API key under Tokens
  2. 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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