Vggt Omega 1B 256 Oxe Mimicgen Rc365 Step23000

Important note: mixed-H training history

• Steps 0–22,000: trained with history_horizon=4 (canonical run config)
• Steps 22,001–23,000: trained with history_horizon=8 via a wrong-defaults resume attempt (job 2331403)

If you intend to use this for further H=4 training, the weights at step 22000 are cleaner. See the matching W&B run summary for per-step metrics.

File

• 0023000.pt — full DeepSpeed-style checkpoint (~12.8 GB, contains model_state, optimizer_state, scheduler_state, step, action/proprio normalizer stats)

--- library_name: pytorch tags: - robotics - depth-estimation - world-model - vggt - 3da license: other --- # VGGT-Omega 1B-256 OxE+MimicGen+RoboCasa365 — step 23000 snapshot Single checkpoint snapshot from the 3DA_unified VGGT-Omega 1B-256 multi-source pretraining run, taken at training step 23,000. ## Provenance - **Run**: `[VGGTOMEGA]_oxe_mimicgen_robocasa365_H8_vggtomega256_text_8n_mb2acc2_compile_2315944` - **W&B run id**: `bags/robot-gld/ohf3lpoa` - **Backbone**: VGGT-Omega 1B (encoder_input_size=256, DINOv3 patch=16) - **Data**: OXE 23-dataset mix + MimicGen + RoboCasa365 (Cosmos24 subset) - **Training**: 8 nodes × 4 GH200 = 32 GPUs, CSCS Clariden ## Important note: mixed-H training history - Steps 0–22,000: trained with `history_horizon=4` (canonical run config) - Steps 22,001–23,000: trained with `history_horizon=8` via a wrong-defaults resume attempt (job `2331403`) If you intend to use this for further H=4 training, the weights at step 22000 are cleaner. See the matching W&B run summary for per-step metrics. ## File - `0023000.pt` — full DeepSpeed-style checkpoint (~12.8 GB, contains `model_state`, `optimizer_state`, `scheduler_state`, `step`, action/proprio normalizer stats)