Instructions to use quadcoders/dqn-smart-energy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use quadcoders/dqn-smart-energy with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="quadcoders/dqn-smart-energy", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
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Download README.md from quadcoders/dqn-smart-energy: direct link, hf CLI and curl.
- Browser
- Download file 577 Bytes
-
https://huggingface.co/quadcoders/dqn-smart-energy/resolve/main/README.md
- Command line
-
hf download hf://quadcoders/dqn-smart-energy/README.md
-
curl -L -o README.md https://huggingface.co/quadcoders/dqn-smart-energy/resolve/main/README.md
577 Bytes
metadata
tags:
- SmartEnergyEnv
- dqn
- reinforcement-learning
- stable-baselines3
model-index:
- name: dqn-smart-energy
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SmartEnergyEnv
type: SmartEnergyEnv
metrics:
- type: mean_reward
value: '-7.62 +/- 0.09'
name: mean_reward
verified: false
DQN Agent playing SmartEnergyEnv
This is a trained model of a DQN agent playing the SmartEnergyEnv environment using the Stable-Baselines3 library.