In this video, Ansh Mehra has come up with ChatGPT Tutorial for Beginners in Hindi. This is a complete Tutorial, and after this you won't be needing another ChatGPT Tutorial…
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Find here pretrained model weights for the [Decision Transformer] (https://github.com/kzl/decision-transformer).
Weights are available for 4 Atari games: Breakout, Pong, Qbert and Seaquest. Found in the checkpoints directory.
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ARCHIVED MODEL, DO NOT USE IT
stable-baselines3-ppo-LunarLander-v2 ππ©βπ
Use the Model
Install the dependencies
Evaluate the agent
Results
model-index:
name: stable-baselines3-ppo-LunarLander-v2
ARCHIVED MODEL, DO NOT USE…
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PPO Agent playing Walker2DBulletEnv-v0
Usage (with Stable-baselines3)
PPO Agent playing Walker2DBulletEnv-v0
This is a trained model of a PPO agent playing Walker2DBulletEnv-v0
using the stable-baselines3 library.…
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ThomasSimonini/ppo-SpaceInvadersNoFrameskip-v4
Usage (with Stable-baselines3)
Evaluation Results
ThomasSimonini/ppo-SpaceInvadersNoFrameskip-v4
This is a pre-trained model of a PPO agent playing SpaceInvadersNoFrameskip using the stable-baselines3 library. It is taken…
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PPO Agent playing SeaquestNoFrameskip-v4
Evaluation Results
Usage (with Stable-baselines3)
Training Code
PPO Agent playing SeaquestNoFrameskip-v4
This is a trained model of a PPO agent playing…
PPO Agent playing QbertNoFrameskip-v4
This is a trained model of a PPO agent playing QbertNoFrameskip-v4 using the stable-baselines3 library.
The training report: https://wandb.ai/simoninithomas/HFxSB3/reports/Atari-HFxSB3-Benchmark--VmlldzoxNjI3NTIy
Evaluation Results
Mean_reward: 15685.00 +/- 115.217
Usage (with Stable-baselines3)
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