akantox/mario-rl-model

Mario PPO Model

This is a PPO agent trained using Stable Baselines3 and Gymnasium on a Mario-like environment.

Environment Details

• Action Space: Simple discrete NES-style actions (7 total)
• Observation: Grayscale, 250×264
• Frame Stack: 4 frames

Training Info

• Algorithm: PPO
• Framework: Stable Baselines3
• Timesteps: 20 million
• Environment: Gymnasium (v0)
• Device: MPS / CUDA / CPU

Training Timesteps & Checkpoints

Checkpoint	Timesteps	Notes
25M Steps	25,000,000	Early-stage learning
50M Steps	50,000,000	Better stability

Usage

from stable_baselines3 import PPO
from huggingface_hub import hf_hub_download

model_path = hf_hub_download(repo_id="akantox/mario-rl-model", filename="mario_ppo.zip")
model = PPO.load(model_path)