Reinforcement Learning
stable-baselines3
Pendulum-v1
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use sb3/ddpg-Pendulum-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use sb3/ddpg-Pendulum-v1 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="sb3/ddpg-Pendulum-v1", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
File size: 406 Bytes
34fd2f5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | !!python/object/apply:collections.OrderedDict
- - - buffer_size
- 200000
- - gamma
- 0.98
- - gradient_steps
- -1
- - learning_rate
- 0.001
- - learning_starts
- 10000
- - n_timesteps
- 20000
- - noise_std
- 0.1
- - noise_type
- normal
- - policy
- MlpPolicy
- - policy_kwargs
- dict(net_arch=[400, 300])
- - train_freq
- - 1
- episode
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