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README.md

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+---
+library_name: pytorch
+tags:
+- autonomous-driving
+- flow-matching
+- occupancy-prediction
+- trajectory-prediction
+- bench2drive
+---
+
+# OCCWAM B2D v9 step18000
+
+This repository contains the deployed OCCWAM joint flow-matching checkpoint
+used by the v9 Bench2Drive closed-loop agent.
+
+## Checkpoint
+
+| Field | Value |
+| --- | --- |
+| File | `v9_step18000/v9step18000_FULL_merged.pt` |
+| Size | 1,656,918,530 bytes |
+| SHA-256 | `43d914c7afa8c892b03023c96a6f3619b1aa37d874e103d28a12824a1c42316f` |
+| Envelope | `occwam-fullmot-best-model-v1` |
+| Global step | 18000 |
+| Config SHA-256 | `7948cd560c83dc2b519be5ff882c5ff68f43daf3456e4fb774d4ae659017651b` |
+
+Training and inference code: <https://github.com/HQH111/OCCWAM>
+
+The inference graph is scene-frame joint OCC/trajectory flow matching from
+white noise, followed by a hard scene-to-future-ego warp, VAE re-encoding and
+one velocity-parameterised ego-rollout refinement.
+
+## Required contract
+
+```bash
+export AEC_TRAJ1_CTX=2
+export AEC_TRAJ2_VFM=1
+export OCCWAM_TP_NORM_UNIFIED=1
+```
+
+The unified target-point normalisation flag must be set at both training and
+inference. Omitting it silently changes the input conditioning.
+
+This checkpoint does not embed the frozen Qwen3-VL, Stage-3 carrier, OCC VAE,
+TransFuser++ and Profile-B assets. Their hashes and roles are documented in the
+GitHub repository's runtime and training configs.
+