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--- |
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datasets: |
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- jakegrigsby/metamon-synthetic |
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- jakegrigsby/metamon-parsed-replays |
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license: apache-2.0 |
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pipeline_tag: reinforcement-learning |
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library_name: amago |
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tags: |
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- pokemon |
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- game-ai |
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- offline-rl |
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- transformers |
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--- |
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Checkpoints from Metamon (v1) training runs. |
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**Metamon** enables reinforcement learning (RL) research on [Pokémon Showdown](https://pokemonshowdown.com/) by providing: |
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1) A standardized suite of teams and opponents for evaluation. |
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2) A large dataset of RL trajectories "reconstructed" from real human battles. |
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3) Starting points for training imitation learning (IL) and RL policies. |
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Metamon is the codebase behind ["Human-Level Competitive Pokémon via Scalable Offline RL and Transformers"](https://arxiv.org/abs/2504.04395) (RLC, 2025). Please check out our [project website](https://metamon.tech) for an overview of our results. This README documents the dataset, pretrained models, training, and evaluation details to help you get battling! |
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**Paper:** [Human-Level Competitive Pokémon via Scalable Offline Reinforcement Learning with Transformers](https://huggingface.co/papers/2504.04395) |
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**Project Website:** https://metamon.tech |
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**Code:** [GitHub Repository](https://github.com/UT-Austin-RPL/metamon/tree/main) |
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### Usage |
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Pretrained models can run without research GPUs, but you will need to install [`amago`](https://github.com/UT-Austin-RPL/amago), which is an RL codebase by the same authors. Follow installation instructions [here](https://ut-austin-rpl.github.io/amago/installation.html). |
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Load and run pretrained models with `metamon.rl.eval_pretrained`. For example, to run the default checkpoint of the `SyntheticRLV2` model for 100 battles against a set of heuristic baselines: |
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```bash |
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python -m metamon.rl.eval_pretrained --agent SyntheticRLV2 --gens 1 --formats ou --n_challenges 100 --eval_type heuristic |
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``` |
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To battle against other models or humans online (via a local Showdown server): |
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```bash |
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python -m metamon.rl.eval_pretrained --agent SyntheticRLV2 --gens 1 --formats ou --n_challenges 50 --eval_type ladder --username <pick unique username> --team_set competitive |
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``` |
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For more details on models and usage, please refer to the [project's GitHub repository](https://github.com/UT-Austin-RPL/metamon/tree/main). |