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zap-thamm/Remote-DQN-Taxi-v3
Remote-DQN-Taxi-v3 is a reinforcement learning model from zap-thamm. 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 an agent playing on the environment Taxi-v3. The agent was trained with a Remote-DQN algorithm and evaluated for 50 episodes. See further agent and evaluation metadata in the according READM…
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Updated Dec 28, 2023
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From the Hugging Face model README
This is a trained model of an agent playing on the environment Taxi-v3. The agent was trained with a Remote-DQN algorithm and evaluated for 50 episodes. See further agent and evaluation metadata in the according README section.
The Python module used for training and uploading/downloading is rl-framework. It is an easy-to-read, plug-and-use Reinforcement Learning framework and provides standardized interfaces and implementations to various Reinforcement Learning methods and environments.
Also it provides connectors for the upload and download to popular model version control systems, including the HuggingFace Hub.
from rl-framework import StableBaselinesAgent, StableBaselinesAlgorithm
# Create new agent instance
agent = StableBaselinesAgent(
algorithm=StableBaselinesAlgorithm.Remote-DQN
algorithm_parameters={
...
},
)
# Download existing agent from HF Hub
repository_id = "zap-thamm/Remote-DQN-Taxi-v3"
file_name = "algorithm.zip"
agent.download(repository_id=repository_id, filename=file_name)
Further examples can be found in the exploration section of the rl-framework repository.