---
license: mit
---

# LeWAM OGBench cube

Goal-reaching checkpoint in the **LeWAM v1 format**. Files are stored at the repository root:

```text
lewam_best.pt
lewam_config.json
```

Download both files into `$STABLEWM_HOME/checkpoints/<run_name>/`, then evaluate with the v1 code:

```bash
python scripts/eval_lewam.py --config-name cube policy=<run_name>
```

The checkpoint was trained with `lewam-jointflow@2d52888` and converted to the v1 schema.
Every retained tensor is exactly equal to the original after renaming; strict model loading,
attention masks, encoder output, supplied-goal action prediction and dynamics prediction passed.
Only the obsolete, all-zero `null_goal` tensor was removed; the original goal-dropout setting was zero.
No optimizer state is included.

Original checkpoint and historical performance: [source repository](https://huggingface.co/datasets/LeWAM/lewam_ckpt_pusht_puzzle_scene_cube_drawer).
Drawer uses goal offset 50 and budget 100; the other tasks use offset 25 and budget 50.

SHA256 of `lewam_best.pt`: `73324009479d18256184d1ac3001254381fb6408aa213301a7c50f4923cf25e1`.