Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use salym/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use salym/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="salym/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from salym/ppo-LunarLander-v2: direct link, hf CLI and curl.
- Browser
- Download file 1.89 kB
-
https://huggingface.co/salym/ppo-LunarLander-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://salym/ppo-LunarLander-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/salym/ppo-LunarLander-v2/resolve/main/vec_normalize.pkl
1.89 kB
- Xet hash:
- 22f0b97dfba717f9aaa28a7835c99866db94f0d5265f6c1c627c52593b8bf737
- Size of remote file:
- 1.89 kB
- SHA256:
- 0aba33dbfc66e8a65983224e9117e23f91446b20739060ad3653876f4876686e
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