ExusBurn / SpaceInvaders

huggingface.co
Total runs: 4
24-hour runs: 0
7-day runs: 2
30-day runs: -1
Model's Last Updated: March 04 2024
reinforcement-learning

Introduction of SpaceInvaders

Model Details of SpaceInvaders

DQN Agent playing SpaceInvadersNoFrameskip-v4

This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4 using the stable-baselines3 library and the RL Zoo .

The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Usage (with SB3 RL Zoo)

RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo
SB3: https://github.com/DLR-RM/stable-baselines3
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib

Install the RL Zoo (with SB3 and SB3-Contrib):

pip install rl_zoo3
# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga ExusBurn -f logs/
python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4  -f logs/

If you installed the RL Zoo3 via pip ( pip install rl_zoo3 ), from anywhere you can do:

python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga ExusBurn -f logs/
python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4  -f logs/
Training (with the RL Zoo)
python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga ExusBurn
Hyperparameters
OrderedDict([('batch_size', 32),
             ('buffer_size', 100000),
             ('env_wrapper',
              ['stable_baselines3.common.atari_wrappers.AtariWrapper']),
             ('exploration_final_eps', 0.01),
             ('exploration_fraction', 0.1),
             ('frame_stack', 4),
             ('gradient_steps', 1),
             ('learning_rate', 0.0001),
             ('learning_starts', 100000),
             ('n_timesteps', 1000000.0),
             ('optimize_memory_usage', False),
             ('policy', 'CnnPolicy'),
             ('target_update_interval', 1000),
             ('train_freq', 4),
             ('normalize', False)])

Environment Arguments

{'render_mode': 'rgb_array'}

Runs of ExusBurn SpaceInvaders on huggingface.co

4
Total runs
0
24-hour runs
0
3-day runs
2
7-day runs
-1
30-day runs

More Information About SpaceInvaders huggingface.co Model

SpaceInvaders huggingface.co

SpaceInvaders huggingface.co is an AI model on huggingface.co that provides SpaceInvaders's model effect (), which can be used instantly with this ExusBurn SpaceInvaders model. huggingface.co supports a free trial of the SpaceInvaders model, and also provides paid use of the SpaceInvaders. Support call SpaceInvaders model through api, including Node.js, Python, http.

SpaceInvaders huggingface.co Url

https://huggingface.co/ExusBurn/SpaceInvaders

ExusBurn SpaceInvaders online free

SpaceInvaders huggingface.co is an online trial and call api platform, which integrates SpaceInvaders's modeling effects, including api services, and provides a free online trial of SpaceInvaders, you can try SpaceInvaders online for free by clicking the link below.

ExusBurn SpaceInvaders online free url in huggingface.co:

https://huggingface.co/ExusBurn/SpaceInvaders

SpaceInvaders install

SpaceInvaders is an open source model from GitHub that offers a free installation service, and any user can find SpaceInvaders on GitHub to install. At the same time, huggingface.co provides the effect of SpaceInvaders install, users can directly use SpaceInvaders installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

SpaceInvaders install url in huggingface.co:

https://huggingface.co/ExusBurn/SpaceInvaders

Url of SpaceInvaders

SpaceInvaders huggingface.co Url

Provider of SpaceInvaders huggingface.co

ExusBurn
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