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@@ -25,13 +25,28 @@ model-index:
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  This is a trained model of a **A2C** agent playing **PandaReachDense-v2**
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  using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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- ## Usage (with Stable-baselines3)
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- TODO: Add your code
 
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- ```python
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- from stable_baselines3 import ...
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- from huggingface_sb3 import load_from_hub
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- ...
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  This is a trained model of a **A2C** agent playing **PandaReachDense-v2**
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  using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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+ The RL Zoo is a training framework for Stable Baselines3
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+ reinforcement learning agents,
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+ with hyperparameter optimization and pre-trained agents included.
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+ ## Usage (with SB3 RL Zoo)
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+ RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
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+ SB3: https://github.com/DLR-RM/stable-baselines3<br/>
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+ SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
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  ```
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+ # Download model and save it into the logs/ folder
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+ python -m rl_zoo3.load_from_hub --algo tqc --env PandaReachDense-v2 -orga sb3 -f logs/
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+ python enjoy.py --algo a2c --env PandaReachDense-v2 -f logs/
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+ ```
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+
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+ ## Training (with the RL Zoo)
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+ ```
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+ python train.py --algo a2c --env PandaReachDense-v2 -f logs/
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+ # Upload the model and generate video (when possible)
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+ python -m rl_zoo3.push_to_hub --algo a2c --env PandaReachDense-v2 -f logs/ -orga sb3
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+ ```
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+
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+
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+ Panda Gym environments: [arxiv.org/abs/2106.13687](https://arxiv.org/abs/2106.13687)