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q-FrozenLake-v1-4x4-noSlippery
Redha-13/q-FrozenLake-v1-4x4-noSlippery
q-FrozenLake-v1-4x4-noSlippery is a reinforcement learning model from Redha-13. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product.
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
Access
Public
Updated Oct 30, 2025
Repo size
915 B
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0
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Repo makeup
Click a slice to open those files.
.mp431.2 KB · 90%
At a glance
- Task
- Reinforcement Learning
- Access
- Public
- Created
- Oct 30, 2025
- Updated
- Oct 30, 2025
- SHA
- a2c4ef46
Model card
From the Hugging Face model README
Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
Usage
model = load_from_hub(repo_id="Redha-13/q-FrozenLake-v1-4x4-noSlippery", 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"])
- Task
- Reinforcement Learning
- Created
- Oct 30, 2025
- Updated
- Oct 30, 2025