Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,35 @@
+---
+tags:
+- FrozenLake-v1-8x8
+- q-learning
+- reinforcement-learning
+- custom-implementation
+model-index:
+- name: q-FrozenLake-v1-8x8-Slippery
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: FrozenLake-v1-8x8
+      type: FrozenLake-v1-8x8
+    metrics:
+    - type: mean_reward
+      value: 0.32 +/- 0.47
+      name: mean_reward
+      verified: false
+---
+
+  # **Q-Learning** Agent playing1 **FrozenLake-v1**
+  This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
+
+  ## Usage
+
+  ```python
+
+  model = load_from_hub(repo_id="MarioBarbeque/q-FrozenLake-v1-8x8-Slippery", filename="q-learning.pkl")
+
+  # Don't forget to check if you need to add additional attributes (is_slippery=False etc)
+  env = gym.make(model["env_id"])
+  ```
+  

q-learning.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:00b545d29a926ec48fc66b841303b4e7e3ac89038beda5de3bda347dc84aecc9
+size 2441

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:950ac3b6de5f8eaf4c5a7bc057f70ad39d25a72061d777bb22a4e7c8eeb653a2
+size 154469

results.json

@@ -0,0 +1 @@
+{"env_id": "FrozenLake-v1", "mean_reward": 0.322, "n_eval_episodes": 1000, "eval_datetime": "2025-07-17T20:20:29.933631"}