Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use erandaheshan43/SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use erandaheshan43/SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="erandaheshan43/SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
File size: 543 Bytes
fcc3944 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | while getopts a:e:s:p: flag
do
case "${flag}" in
a) algo=${OPTARG};;
e) envs=${OPTARG};;
s) seeds=${OPTARG};;
p) project_name=${OPTARG};;
esac
done
WANDB_TAGS=$(bash scripts/tags_benchmark.sh)
project_name="${project_name:-rl-algo-impls-benchmarks}"
seeds="${seeds:-1 2 3}"
for env in $(echo $envs); do
for seed in $seeds; do
echo python train.py --algo $algo --env $env --seed $seed --pool-size 1 --wandb-tags $WANDB_TAGS --wandb-project-name $project_name --virtual-display
done
done
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