Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use saisowrya/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use saisowrya/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="saisowrya/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4 using the stable-baselines3 library and the RL Zoo.
Evaluation Results
- Mean Reward: 680.00 +/- 231.26
- Score (mean - std): 448.74 (Required: >= 200.0)
Usage
from stable_baselines3 import DQN
from huggingface_sb3 import load_from_hub
repo_id = "saisowrya/dqn-SpaceInvadersNoFrameskip-v4"
filename = "dqn-SpaceInvadersNoFrameskip-v4.zip"
model = load_from_hub(repo_id=repo_id, filename=filename)
- Downloads last month
- 6
Evaluation results
- mean_reward on SpaceInvadersNoFrameskip-v4self-reported680.00 +/- 231.26