|
--- |
|
library_name: stable-baselines3 |
|
tags: |
|
- AntBulletEnv-v0 |
|
- deep-reinforcement-learning |
|
- reinforcement-learning |
|
- stable-baselines3 |
|
model-index: |
|
- name: A2C |
|
results: |
|
- metrics: |
|
- type: mean_reward |
|
value: 2124.31 +/- 153.87 |
|
name: mean_reward |
|
task: |
|
type: reinforcement-learning |
|
name: reinforcement-learning |
|
dataset: |
|
name: AntBulletEnv-v0 |
|
type: AntBulletEnv-v0 |
|
--- |
|
|
|
# **A2C** Agent playing **AntBulletEnv-v0** |
|
This is a trained model of a **A2C** agent playing **AntBulletEnv-v0** |
|
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 |
|
|
|
... |
|
``` |
|
|
