Reinforcement Learning
stable-baselines3
deep-reinforcement-learning
agricultural-ai
weather-modelling
curriculum-learning
edge-ai
Instructions to use DHDRL/monsoon-rl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use DHDRL/monsoon-rl with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="DHDRL/monsoon-rl", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
| [build-system] | |
| requires = ["setuptools>=61"] | |
| build-backend = "setuptools.build_meta" | |
| [project] | |
| name = "monsoon-rl" | |
| version = "0.3.0" | |
| description = "Agricultural weather-risk RL (MaskablePPO + zone-equivariant GRU) for Indonesian rice zones" | |
| readme = "README.md" | |
| requires-python = ">=3.10" | |
| license = { text = "AGPL-3.0-or-later" } | |
| authors = [{ name = "DHDRL" }] | |
| dependencies = [ | |
| "numpy>=1.24", | |
| "torch>=2.0", | |
| "gymnasium>=0.29", | |
| "stable-baselines3>=2.0", | |
| "sb3-contrib>=2.0", | |
| ] | |
| optional-dependencies = { edge = ["onnx>=1.15"], mqtt = ["paho-mqtt>=1.6"], dev = ["pytest>=7.0", "optuna>=3.5"] } | |
| [project.urls] | |
| Repository = "https://huggingface.co/DHDRL/monsoon-rl" | |
| [tool.setuptools] | |
| py-modules = [ | |
| "zone_observation", | |
| "crop_risk_scorer", | |
| "weather_forecast_env", | |
| "gru_weather_policy", | |
| "climatology", | |
| "indonesia_zones", | |
| "physics_dynamics", | |
| "product_alert_service", | |
| "impact_labels", | |
| "mnn_export", | |
| "train_kaggle", | |
| "train_curriculum", | |
| ] | |