metadata
library_name: stable-baselines3
tags:
- CartPole-v1
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: MlpPolicy
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_reward
value: 500.00 +/- 0.00
name: mean_reward
verified: false
MlpPolicy Agent playing CartPole-v1
This is a trained model of a MlpPolicy agent playing CartPole-v1 using the stable-baselines3 library.
Usage (with Stable-baselines3)
from stable_baselines3 import A2C
from huggingface_sb3 import load_from_hub
checkpoint = load_from_hub(
repo_id="thomasbar/a2c_sb3_cartpole",
filename="a2c_sb3_cartpole.zip",
)
model = A2C.load(checkpoint)