A2C-Atari-Pong / README.md
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---
library_name: stable-baselines3
tags:
- PongNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PongNoFrameskip-v4
type: PongNoFrameskip-v4
metrics:
- type: mean_reward
value: -20.90 +/- 0.30
name: mean_reward
verified: false
---
# **A2C** Agent playing **PongNoFrameskip-v4**
This is a trained model of a **A2C** agent playing **PongNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
```