Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use dcarpintero/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use dcarpintero/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="dcarpintero/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download ppo-LunarLander-v2.zip from dcarpintero/ppo-LunarLander-v2: direct link, hf CLI and curl.
- Browser
- Download file 147 kB
-
https://huggingface.co/dcarpintero/ppo-LunarLander-v2/resolve/main/ppo-LunarLander-v2.zip
- Command line
-
hf download hf://dcarpintero/ppo-LunarLander-v2/ppo-LunarLander-v2.zip
-
curl -L -o ppo-LunarLander-v2.zip https://huggingface.co/dcarpintero/ppo-LunarLander-v2/resolve/main/ppo-LunarLander-v2.zip
147 kB
- Xet hash:
- 60552ac47298ac54913c68cad189717ec821e650f5bbc82091a78aceffd87558
- Size of remote file:
- 147 kB
- SHA256:
- 407608fe90ff13cacd89644a6df59eb97af9468bab1d7091ba52694b833db07b
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