A2c PandaReachDense v3 | Sweet Tea StudioA2c PandaReachDense v3
This is a trained model of a A2C agent playing PandaReachDense-v3 using the stable-baselines3 library. Usage (with Stable-baselines3)
Verified source
Kindreinforcement-learningVersionv044987dd486daba2d669a102645238d9fc682661Publisher@Stilt34Cgrade Model source
- Kind
- reinforcement-learning
- Version
- v044987dd486daba2d669a102645238d9fc682661
- Source
- Hugging Face
--- library_name: stable-baselines3 tags: - PandaReachDense-v3 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: A2C results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: PandaReachDense-v3 type: PandaReachDense-v3 metrics: - type: mean_reward value: -0.23 +/- 0.11 name: mean_reward verified: false --- # **A2C** Agent playing **PandaReachDense-v3** This is a trained model of a **A2C** agent playing **PandaReachDense-v3** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
Sources & provenance
1 active source
Source evidence
3 excerpts
libraryname: stable-baselines3 tags: PandaReachDense-v3 deep-reinforcement-learning reinforcement-learning stable-baselines3 model-index: name: A2C results: task: type: reinforcement-learning name: reinforcement-learning dataset: name: PandaReachDense-v3…
Jul 11
This is a trained model of a A2C agent playing PandaReachDense-v3 using the stable-baselines3 library. Usage (with Stable-baselines3)
Stilt34/a2c-PandaReachDense-v3