Reinforcement Learning
stable-baselines3
English
sb3-contrib
gymnasium
maskable-ppo
utdg
tower-defense
game-ai
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use chrisjcc/utdg-maskableppo-policy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use chrisjcc/utdg-maskableppo-policy with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="chrisjcc/utdg-maskableppo-policy", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download models/model_policy.zip from chrisjcc/utdg-maskableppo-policy: direct link, hf CLI and curl.
- Browser
- Download file 650 kB
-
https://huggingface.co/chrisjcc/utdg-maskableppo-policy/resolve/main/models/model_policy.zip
- Command line
-
hf download hf://chrisjcc/utdg-maskableppo-policy/models/model_policy.zip
-
curl -L -o model_policy.zip https://huggingface.co/chrisjcc/utdg-maskableppo-policy/resolve/main/models/model_policy.zip
650 kB
- Xet hash:
- e35466ee779d747cfb8cf27912bba9f4da186b6da7b1dfffe986ac388d65b7d0
- Size of remote file:
- 650 kB
- SHA256:
- f34808d6a93d57b8f796064f0afb4e346da4fa9c0f0f926031df6cb0c52d0beb
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