Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use bojanb/rl-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use bojanb/rl-test with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="bojanb/rl-test", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download test/policy.optimizer.pth from bojanb/rl-test: direct link, hf CLI and curl.
- Browser
- Download file 88.4 kB
-
https://huggingface.co/bojanb/rl-test/resolve/main/test/policy.optimizer.pth
- Command line
-
hf download hf://bojanb/rl-test/test/policy.optimizer.pth
-
curl -L -o policy.optimizer.pth https://huggingface.co/bojanb/rl-test/resolve/main/test/policy.optimizer.pth
88.4 kB
- Xet hash:
- b6a037711cbfd13efa62cec8c68614729e8f1d95daff5ec1c9827f7ab6764d8d
- Size of remote file:
- 88.4 kB
- SHA256:
- e7e778a5eb4ee79d2768d3c5dc6b0ffe1cc800240dae4702e92ab61c4811d576
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.