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Paths in this model repository match paths relative to `learning/policies/` in the code repository. The top-level domains are `coffee_box`, `coffee_drawer`, `kitchen`, and `nut_assembly`; the original task, algorithm, training configuration, and seed subfolders are preserved. Only model checkpoint ZIP files are included: `final_model.zip`, `best_model.zip`, and `recent_model.zip`. Training/evaluation logs, replay buffers, and executor files are not included.

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ppo-Pendulum-v1

HumanCompatibleAI

This is a trained model of a **PPO** agent playing **Pendulum-v1** using the stable-baselines3 library and the RL Zoo. The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo SB3: https://github.com/DLR-RM/stable-baselines3 SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib

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ppo-seals-CartPole-v0

HumanCompatibleAI

This is a trained model of a **PPO** agent playing **seals/CartPole-v0** using the stable-baselines3 library and the RL Zoo. The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo SB3: https://github.com/DLR-RM/stable-baselines3 SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib

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goi-rl

miiwater

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AdaGuard-8B-GGUF

mradermacher

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AesCode-32B-GGUF

mradermacher

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AesCode-8B-GGUF

mradermacher

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AesCode-8B-i1-GGUF

mradermacher

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Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

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