ppo-Huggy is an open-source reinforcement learning model designed for use with ML-Agents environments. It supports integration with ML-Agents, ONNX export, and TensorBoard visualization, making it suitable for researchers and developers working on RL projects.
Ppo Huggy is an Other AI product. It focuses on providing a pre-trained reinforcement learning agent for ML-Agents environments to accelerate RL experimentation. It is built as an open-source project for machine learning researchers and developers. Ppo Huggy is open source under the Open Source license. The product ships for the web, API, and the command line.
Behind Ppo Huggy is modeliqi, and the product first shipped in 2017. Development happens publicly on GitHub with 19.6k stars and 16 commits in the last 90 days. PulseGate's similarity index finds few close equivalents — Ppo Huggy occupies a relatively distinct niche. Key capabilities include reinforcement learning, ML-Agents integration, and tensorBoard support.
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modeliqi/ppo-Huggy discovered by the PulseGate indexer
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