Reinforcement Learning
Transformers
TensorBoard
LunarLander-v2
ppo
deep-reinforcement-learning
custom-implementation
deep-rl-course
Eval Results (legacy)
Instructions to use rootacess/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rootacess/ppo-LunarLander-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rootacess/ppo-LunarLander-v2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- LunarLander-v2
- ppo
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
- deep-rl-course
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
metrics:
- type: mean_reward
value: '-158.03 +/- 64.23'
name: mean_reward
verified: false
PPO Agent Playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2.