Reinforcement Learning
Transformers
TensorBoard
LunarLander-v2
ppo
deep-reinforcement-learning
custom-implementation
deep-rl-course
Eval Results (legacy)
Instructions to use Isaacp/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isaacp/ppo-LunarLander-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Isaacp/ppo-LunarLander-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 770b875e54ca58e411062a9f7484eb0aa15130d23cfbf1e746cec0e19a6449df
- Size of remote file:
- 42.6 kB
- SHA256:
- db8226ec4a337291f8702e955626af7f114545b762f2d8cfdbabd27b045ac2a0
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