Reinforcement Learning
stable-baselines3
TensorBoard
LunarLander-v2
ppo
deep-reinforcement-learning
deep-rl-course
Eval Results (legacy)
Instructions to use Akshaykumar4321/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Akshaykumar4321/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Akshaykumar4321/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download config.json from Akshaykumar4321/ppo-LunarLander-v2: direct link, hf CLI and curl.
- Browser
- Download file 202 Bytes
-
https://huggingface.co/Akshaykumar4321/ppo-LunarLander-v2/resolve/main/config.json
- Command line
-
hf download hf://Akshaykumar4321/ppo-LunarLander-v2/config.json
-
curl -L -o config.json https://huggingface.co/Akshaykumar4321/ppo-LunarLander-v2/resolve/main/config.json
202 Bytes
| { | |
| "algo": "PPO", | |
| "env_id": "LunarLander-v2", | |
| "n_steps": 1024, | |
| "batch_size": 64, | |
| "n_epochs": 4, | |
| "gamma": 0.999, | |
| "gae_lambda": 0.98, | |
| "ent_coef": 0.01, | |
| "learning_rate": 0.0003 | |
| } |