---
tags:
- ppo
- reinforcement-learning
- swarm
- drone
- bittensor
license: mit
language:
- en
library_name: stable-baselines3
---

# 🚀 Swarm PPO Drone

This repository contains a **Proximal Policy Optimization (PPO)** model trained for **swarm/drone control**.  
The model was trained using **Gymnasium environments** with Stable-Baselines3 and exported for use in **Bittensor Subnet 124 (Swarm)**.

---

## 📂 Files

- `policy.pth` – Trained PPO policy weights (PyTorch).
- `ppo_policy.zip` – Stable-Baselines3 PPO saved model (reload with `PPO.load()`).
- `safe_policy_meta.json` – Metadata for policy compliance.
- `best/` – Best checkpointed model during training.
- `eval_logs/` – Evaluation logs.
- `tb_logs/` – TensorBoard logs.

---

## 🛠️ Usage

### Load with Stable-Baselines3
```python
from stable_baselines3 import PPO
import gymnasium as gym

# Load model
model = PPO.load("ppo_policy.zip")

# Example run
env = gym.make("CartPole-v1")
obs, _ = env.reset()
action, _ = model.predict(obs)
print("Predicted action:", action)