README.md

---
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](https://github.com/DLR-RM/stable-baselines3).

## Usage (with Stable-baselines3)
```python
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)
```