Add pretrained FMQ checkpoints (12 envs x 5 seeds)

README.md

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+---
+license: mit
+tags:
+  - reinforcement-learning
+  - offline-rl
+  - flow-matching
+  - robotics
+  - jax
+datasets:
+  - ogbench
+  - robomimic
+---
+
+# Flow Map Policies — Pretrained FMQ Checkpoints
+
+Pretrained checkpoints for **"Aligning Flow Map Policies with Optimal Q-Guidance"**.
+
+**Paper:** [arXiv:2605.12416](https://arxiv.org/abs/2605.12416)  
+**Code:** [github.com/christoszi/flow-map-policies](https://github.com/christoszi/flow-map-policies)
+
+## Model Description
+
+These are Flow Map Q-Guidance (FMQ) agents trained with offline-to-online RL. Each checkpoint contains a flow map policy fine-tuned online for 1M steps using critic-guided trust-region optimization.
+
+## Checkpoints
+
+12 environments x 5 random seeds = 60 checkpoints total.
+
+| Folder | Environment | Benchmark |
+|--------|-------------|-----------|
+| `checkpoints/ctrp4/` | cube-triple-play-singletask-task4-v0 | OGBench |
+| `checkpoints/ctrp3/` | cube-triple-play-singletask-task3-v0 | OGBench |
+| `checkpoints/cdp4/` | cube-double-play-singletask-task4-v0 | OGBench |
+| `checkpoints/cdp3/` | cube-double-play-singletask-task3-v0 | OGBench |
+| `checkpoints/sc4/` | scene-play-singletask-task4-v0 | OGBench |
+| `checkpoints/sc5/` | scene-play-singletask-task5-v0 | OGBench |
+| `checkpoints/ag4/` | antmaze-giant-navigate-singletask-task4-v0 | OGBench |
+| `checkpoints/ag5/` | antmaze-giant-navigate-singletask-task5-v0 | OGBench |
+| `checkpoints/hm3/` | humanoidmaze-medium-navigate-singletask-task3-v0 | OGBench |
+| `checkpoints/hm4/` | humanoidmaze-medium-navigate-singletask-task4-v0 | OGBench |
+| `checkpoints/can/` | can-mh-low_dim | RoboMimic |
+| `checkpoints/square/` | square-mh-low_dim | RoboMimic |
+
+## Usage
+
+```bash
+pip install huggingface_hub
+python -c "from huggingface_hub import snapshot_download; snapshot_download('christoszi/flow-map-policies', local_dir='.')"
+```
+
+Then evaluate:
+
+```bash
+python main.py --config configs/config.yaml \
+  --eval_only --fmq_online \
+  --restore_path=checkpoints/ctrp4/params_online_sd000.pkl \
+  --env_name=cube-triple-play-singletask-task4-v0 --seed=0
+```
+
+## Citation
+
+```bibtex
+@article{ziakas2026fmq,
+  title={Aligning Flow Map Policies with Optimal Q-Guidance},
+  author={Ziakas, Christos and Russo, Alessandra and Bose, Avishek Joey},
+  journal={arXiv preprint arXiv:2605.12416},
+  year={2026},
+}
+```