Views
No views yet
pip install rl_zoo3# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo ars --env Walker2DBulletEnv-v0 -orga qgallouedec -f logs/
python -m rl_zoo3.enjoy --algo ars --env Walker2DBulletEnv-v0 -f logs/pip install rl_zoo3), from anywhere you can do:python -m rl_zoo3.load_from_hub --algo ars --env Walker2DBulletEnv-v0 -orga qgallouedec -f logs/
python -m rl_zoo3.enjoy --algo ars --env Walker2DBulletEnv-v0 -f logs/python -m rl_zoo3.train --algo ars --env Walker2DBulletEnv-v0 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo ars --env Walker2DBulletEnv-v0 -f logs/ -orga qgallouedec1OrderedDict([('alive_bonus_offset', -1),
2 ('delta_std', 0.025),
3 ('learning_rate', 0.03),
4 ('n_delta', 40),
5 ('n_timesteps', 75000000.0),
6 ('n_top', 30),
7 ('normalize', 'dict(norm_obs=True, norm_reward=False)'),
8 ('policy', 'MlpPolicy'),
9 ('policy_kwargs', 'dict(net_arch=[64, 64])'),
10 ('zero_policy', False),
11 ('normalize_kwargs', {'norm_obs': True, 'norm_reward': False})])