Reinforcement Learning
stable-baselines3
AntBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Sekiraw/Ant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Sekiraw/Ant with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Sekiraw/Ant", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Update results.json
Browse files- results.json +1 -1
results.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"mean_reward": 2548.3274639207402, "std_reward": 83.37114007524761, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-
|
|
|
|
| 1 |
+
{"mean_reward": 2548.3274639207402, "std_reward": 83.37114007524761, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-18T17:48:30.568530"}
|