Instructions to use andrewzhang505/sample-factory-2-mujoco-pendulum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use andrewzhang505/sample-factory-2-mujoco-pendulum with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r andrewzhang505/sample-factory-2-mujoco-pendulum -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
metadata
library_name: sample-factory
tags:
- deep-reinforcement-learning
- reinforcement-learning
- sample-factory
model-index:
- name: APPO
results:
- metrics:
- type: mean_reward
value: 1000.00 +/- 0.00
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: mujoco_pendulum
type: mujoco_pendulum
A(n) APPO model trained on the mujoco_pendulum environment. This model was trained using Sample Factory 2.0: https://github.com/alex-petrenko/sample-factory