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rr-item-4p-v1
vlabki/rr-item-4p-v1
rr-item-4p-v1 is a reinforcement learning model from vlabki. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch.
Self-contained recurrent player-policy checkpoint.
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At a glance
- Task
- Reinforcement Learning
- Library
- pytorch
- Model type
- rr_player_recurrent_bc
- Access
- Public
- Created
- Sep 3, 2026
- Updated
- Sep 3, 2026
- SHA
- d5f8574a
Model card
From the Hugging Face model README
vlabki/rr-item-4p-v1
Self-contained recurrent player-policy checkpoint.
- Source directory:
last - PPO update: 1900
- Environment steps: 23347200
- Action support: wheelie
Evaluation values below come from deterministic fixed-seed argmax runs. Frame averages exclude DNF races.
Best reliable evaluation
No completed fixed-seed evaluation recorded.
Best fastest evaluation
No completed fixed-seed evaluation recorded.
Files
Runtime weights, model config, normalization statistics, route reference, training config, and portable checksummed fallbacks are included. Raw rollout traces, optimizer state, and full training logs are excluded.
- Task
- Reinforcement Learning
- Library
- pytorch
- Type
- rr_player_recurrent_bc
- Created
- Sep 3, 2026
- Updated
- Sep 3, 2026