Add files

README.md

@@ -1,3 +1,86 @@
 ---
-license: mit
+library_name: skrl
+tags:
+- deep-reinforcement-learning
+- reinforcement-learning
+- skrl
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: -38.54 +/- 17.49
+      name: Total reward (mean)
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: IsaacGymEnvs-FactoryTaskNutBoltPlace
+      type: IsaacGymEnvs-FactoryTaskNutBoltPlace
 ---
+
+<!-- ---
+torch: -38.54 +/- 17.49
+jax: -60.9 +/- 0.84
+numpy: -58.9 +/- 1.8
+--- -->
+
+# IsaacGymEnvs-FactoryTaskNutBoltPlace-PPO
+
+Trained agent for [NVIDIA Isaac Gym Preview](https://github.com/NVIDIA-Omniverse/IsaacGymEnvs) environments.
+
+- **Task:** FactoryTaskNutBoltPlace
+- **Agent:** [PPO](https://skrl.readthedocs.io/en/latest/api/agents/ppo.html)
+
+# Usage (with skrl)
+
+Note: Visit the skrl [Examples](https://skrl.readthedocs.io/en/latest/intro/examples.html) section to access the scripts.
+
+* PyTorch
+
+    ```python
+    from skrl.utils.huggingface import download_model_from_huggingface
+
+    # assuming that there is an agent named `agent`
+    path = download_model_from_huggingface("skrl/IsaacGymEnvs-FactoryTaskNutBoltPlace-PPO", filename="agent.pt")
+    agent.load(path)
+    ```
+
+* JAX
+
+    ```python
+    from skrl.utils.huggingface import download_model_from_huggingface
+
+    # assuming that there is an agent named `agent`
+    path = download_model_from_huggingface("skrl/IsaacGymEnvs-FactoryTaskNutBoltPlace-PPO", filename="agent.pickle")
+    agent.load(path)
+    ```
+
+# Hyperparameters
+
+Note: Undefined parameters keep their values by default.
+
+```python
+# https://skrl.readthedocs.io/en/latest/api/agents/ppo.html#configuration-and-hyperparameters
+cfg = PPO_DEFAULT_CONFIG.copy()
+cfg["rollouts"] = 120  # memory_size
+cfg["learning_epochs"] = 8
+cfg["mini_batches"] = 30  # 120 * 128 / 512
+cfg["discount_factor"] = 0.99
+cfg["lambda"] = 0.95
+cfg["learning_rate"] = 1e-4
+cfg["random_timesteps"] = 0
+cfg["learning_starts"] = 0
+cfg["grad_norm_clip"] = 0
+cfg["ratio_clip"] = 0.2
+cfg["value_clip"] = 0.2
+cfg["clip_predicted_values"] = True
+cfg["entropy_loss_scale"] = 0.0
+cfg["value_loss_scale"] = 1.0
+cfg["kl_threshold"] = 0.016
+cfg["rewards_shaper"] = None
+cfg["state_preprocessor"] = RunningStandardScaler
+cfg["state_preprocessor_kwargs"] = {"size": env.observation_space, "device": device}
+cfg["value_preprocessor"] = RunningStandardScaler
+cfg["value_preprocessor_kwargs"] = {"size": 1, "device": device}
+```

agent.pickle

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:45e4adf79f0848dfa96397bf0fb37d7e5663ad921b558f414e883588bf4ac3de
+size 1172233

agent.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:086651b9c749d94cab416632d3ebbef2055a7c489d1c153f3d9613e0c715911e
+size 606990