Initial commit

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- PandaReachDense-v3
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: SAC
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: PandaReachDense-v3
+      type: PandaReachDense-v3
+    metrics:
+    - type: mean_reward
+      value: -0.26 +/- 0.10
+      name: mean_reward
+      verified: false
+---
+
+# **SAC** Agent playing **PandaReachDense-v3**
+This is a trained model of a **SAC** agent playing **PandaReachDense-v3**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

SAC-PandaReachDense-v3.zip

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SAC-PandaReachDense-v3/_stable_baselines3_version

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+2.3.2

SAC-PandaReachDense-v3/actor.optimizer.pth

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SAC-PandaReachDense-v3/critic.optimizer.pth

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SAC-PandaReachDense-v3/data

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+        "__module__": "stable_baselines3.sac.policies",
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SAC-PandaReachDense-v3/system_info.txt

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+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.3.2
+- PyTorch: 2.3.0+cu121
+- GPU Enabled: False
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.29.1
+- OpenAI Gym: 0.25.2

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results.json

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