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MBPO-ReacherV5
winkin119/MBPO-ReacherV5
MBPO-ReacherV5 is a reinforcement learning model from winkin119. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product.
This is a trained model of a MBPO agent playing Reacher-v5.
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At a glance
- Task
- Reinforcement Learning
- Access
- Public
- Created
- Sep 1, 2025
- Updated
- Sep 1, 2025
- SHA
- ae6278cb
Model card
From the Hugging Face model README
MBPO Agent playing Reacher-v5
This is a trained model of a MBPO agent playing Reacher-v5.
Usage
create the conda env in https://github.com/GeneHit/drl_practice
conda create -n drl python=3.12
conda activate drl
python -m pip install -r requirements.txt
play with full model
# load the full model
model = load_from_hub(repo_id="winkin119/MBPO-ReacherV5", filename="full_model.pt")
# Create the environment.
env = gym.make("Reacher-v5")
state, _ = env.reset()
action = model.action(state)
...
There is also a state dict version of the model, you can check the corresponding definition in the repo.
- Task
- Reinforcement Learning
- Created
- Sep 1, 2025
- Updated
- Sep 1, 2025