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
Download scripts/train_loop.sh from erandaheshan43/SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 543 Bytes
-
https://huggingface.co/erandaheshan43/SpaceInvadersNoFrameskip-v4/resolve/main/scripts/train_loop.sh
- Command line
-
hf download hf://erandaheshan43/SpaceInvadersNoFrameskip-v4/scripts/train_loop.sh
-
curl -L -o train_loop.sh https://huggingface.co/erandaheshan43/SpaceInvadersNoFrameskip-v4/resolve/main/scripts/train_loop.sh
543 Bytes
| 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 | |