G.O.D Subnet
🚀 Welcome to the [Gradients on Demand](https://gradients.io) Subnet
> Distributed intelligence for LLM and diffusion model training. Where the world's best AutoML minds compete.
**Tournaments** 🏆
Competitive events where the validator executes miners' open-source training scripts on dedicated infrastructure.
- **Schedule**: Environment tournaments start Mondays at 14:00 UTC; text tournaments start Thursdays at 14:00 UTC; image tournaments start Thursdays at 15:00 UTC.
- **Rewards**: Exponentially higher weight potential for top performers
- **Open Source**: Winning AutoML scripts are released when tournaments complete
- **Winners Repository**: First place tournament scripts is uploaded to [github.com/gradients-opensource](https://github.com/gradients-opensource) 🤙
- [Miner Guide](docs/miners.md)
## Setup Guides
- [Miner Guide](docs/miners.md)
- [Validator Setup Guide](docs/validator_setup.md)
## Developer Resources
For technical documentation on GRPO reward functions and implementation details, see [GRPO Safe Code Execution Guide](docs/grpo_rewards_code_execution.md).
## Running evaluations on your own
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.
```bash
docker build -f dockerfiles/validator.dockerfile -t weightswandering/tuning_vali:latest .
docker build -f dockerfiles/validator-diffusion.dockerfile -t diagonalge/tuning_validator_diffusion:latest .
```
To see the available options, run:
```bash
python -m utils.run_evaluation --help
```
To re-evaluate a task, run:
```bash
python -m utils.run_evaluation --task_id
```
To re-evaluate a PvP environment task for selected hotkeys, run:
```bash
python -m utils.run_evaluation --task_id --gpu_ids 0 1 --hotkeys
```
To run a non-submitted model, run:
```bash
python -m utils.run_evaluation --task_id --models
```