Instructions to use Subhash3008/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Subhash3008/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Subhash3008/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
File size: 674 Bytes
9dc7318 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ---
tags:
- reinforcement-learning
- LunarLander-v2
- stable-baselines3
- deep-rl-course
model-index:
- name: ppo-LunarLander-v2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
metrics:
- type: mean_reward
value: 285.4 +/- 12.1
name: mean_reward
---
# PPO LunarLander-v2
This is a trained model for the **Hugging Face Deep Reinforcement Learning Course**.
- **Environment**: `LunarLander-v2`
- **Library**: `stable-baselines3`
- **Evaluation Score**: `285.4 +/- 12.1`
Trained and submitted by **Subhash3008**.
|