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Download README.md from NeoCodes-dev/Taxi_env_Unit2: direct link, hf CLI and curl.
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https://huggingface.co/NeoCodes-dev/Taxi_env_Unit2/resolve/main/README.md
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hf download hf://NeoCodes-dev/Taxi_env_Unit2/README.md
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curl -L -o README.md https://huggingface.co/NeoCodes-dev/Taxi_env_Unit2/resolve/main/README.md
744 Bytes
metadata
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi_env_Unit2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- 2.71
name: mean_reward
verified: false
Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
Usage
model = load_from_hub(repo_id="dergky1/Taxi_env_Unit2", 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"])