G.O.D Subnet

Welcome to the Gradients on Demand subnet.

G.O.D is the subnet runtime behind Gradients.io training jobs and tournaments. Validators create tasks, coordinate miner and trainer infrastructure, evaluate results, and set weights. Miners expose training repositories for tournament tasks; trainers run those repositories on validator-controlled GPU infrastructure.

Tournaments

Tournaments are recurring competitions where miners submit open-source training code. The validator asks each miner for a repository and exact commit, validates the repository, runs the code on dedicated trainers, evaluates the resulting models, and advances winners through tournament rounds.

Tournament types are scheduled independently:

Scheduling notes:

• The scheduler creates a new pending tournament only when there is no pending or active tournament of the same type.
• Follow-up tournaments are created only during the configured UTC start hour. If the window is missed, the next opportunity is the following week's window.
• Tournament length is round- and task-dependent rather than a fixed 4-7 day duration. Pending tournaments collect and validate participants, deduct fees, and activate after the minimum miner count is met; active tournaments advance as training and evaluation rounds finish.
• Text and image tournaments use group, knockout/final, and boss/champion rounds. Environment tournaments use PvP-style evaluation and environment-specific boss comparisons.
• Winning repositories are published to github.com/gradients-opensource, and tournament performance feeds validator weight setting.

Useful public endpoints:

curl https://api.gradients.io/v1/tournaments/next-dates
curl https://api.gradients.io/v1/tournaments/active
curl https://api.gradients.io/v1/tournaments/latest/details
curl https://api.gradients.io/tournament/fees

Documentation

• Developer Guide: repo layout, setup, validator/trainer/miner operations, tests, and common development workflows.
• Miner Guide: miner participation requirements, training repository contract, tournament types, and scoring expectations.

Running Evaluations

You can re-evaluate existing tasks on your own machine. Or you can run non-submitted models to check if they are good. This works for tasks not older than 7 days.

Make sure to build the latest docker images before running the evaluation.

docker build -f ops/docker/validator.dockerfile -t weightswandering/tuning_vali:latest .
docker build -f ops/docker/validator-diffusion.dockerfile -t diagonalge/tuning_validator_diffusion:latest .

To see the available options, run:

python -m ops.validator_ops.run_evaluation --help

To re-evaluate a task, run:

python -m ops.validator_ops.run_evaluation --task_id <task_id>

To re-evaluate a PvP environment task for selected hotkeys, run:

python -m ops.validator_ops.run_evaluation --task_id <task_id> --gpu_ids 0 1 --hotkeys <hotkey_a> <hotkey_b>

To run a non-submitted model, run:

python -m ops.validator_ops.run_evaluation --task_id <task_id> --models <model_name>