Instructions to use garvitsachdeva/spindleflow-rl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use garvitsachdeva/spindleflow-rl with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="garvitsachdeva/spindleflow-rl", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| tags: | |
| - reinforcement-learning | |
| - stable-baselines3 | |
| - sb3-contrib | |
| - gymnasium | |
| - multi-agent | |
| - openenv | |
| library_name: stable-baselines3 | |
| # SpindleFlow RL — Delegation Policy | |
| LSTM PPO agent trained on SpindleFlow-v0 (OpenEnv). | |
| ## Training summary | |
| | Metric | Value | | |
| |---|---| | |
| | Algorithm | RecurrentPPO (SB3 + sb3-contrib) | | |
| | Total timesteps | 30,000 | | |
| | Episodes completed | 13526 | | |
| | First-5 mean reward | 1.2053 | | |
| | Last-5 mean reward | 2.2038 | | |
| | Improvement | +0.9984 | | |
| | Device | cuda | | |
|  | |
| ## Load | |
| ```python | |
| from sb3_contrib import RecurrentPPO | |
| from huggingface_hub import hf_hub_download | |
| model = RecurrentPPO.load(hf_hub_download("garvitsachdeva/spindleflow-rl", "spindleflow_model.zip")) | |
| ``` | |