---
license: other
license_name: openmdw-1.1
license_link: LICENSE
base_model: nvidia/Cosmos3-Nano
tags:
  - robotics
  - cosmos
  - world-model
  - action
  - dk1
  - lerobot
---

# cosmos3-dk1-cartesian

Fine-tune of **NVIDIA Cosmos3-Nano** on the **DK-1 bimanual robot** datamix —
multi-mode world + action SFT with a **cartesian end-effector action space**
(single-step SE(3) pose deltas, à la the Cosmos DROID layout). Checkpoint at
**iter 10000**.

> ⚠️ **This is a DELTA, not a standalone model.** It contains only the ~1.56 B
> *trained* parameters and must be applied on top of the public
> [`nvidia/Cosmos3-Nano`](https://huggingface.co/nvidia/Cosmos3-Nano) base
> (the other ~13.6 B params are frozen and not included here).

## What's in here

| file | what |
|---|---|
| `cosmos3-dk1-cartesian-delta.safetensors` | the 1.555 B trained params (bf16, 3.1 GB) |
| `merge_delta.py` | fold this delta into a base Cosmos3-Nano → **stock-architecture** checkpoint |
| `lora_config.json` | gen-MLP LoRA config (r16 / α32 / targets) |
| `dk1_action_normalization_cartesian.json` | quantile q01/q99 stats for the 20-D cartesian action |

**Trained parameters** (365 tensors, 1,555,175,424 params):
- **Gen attention** `q/k/v/o_proj_moe_gen` — **full fine-tuned** (1.51 B). Existing base modules, trained in place.
- **Action I/O** `action2llm` / `llm2action` / `action_modality_embed` — **full fine-tuned** (17 M). Existing base modules.
- **Gen MLP** `mlp_moe_gen.{gate,up,down}_proj` — **LoRA r16** (28 M adapters, `lora_*` keys). The *only* structurally-new keys.

## Compatibility (loads in the stock Cosmos framework)

The architecture is **identical to Cosmos3-Nano** — our additions are full-FT of
existing modules or extra LoRA keys, never shape changes:

- The full-FT parts (98% of the fine-tuning) load **directly** into a vanilla base
  (same keys/shapes; overwrite values).
- The LoRA adapters are the only extra keys. Either inject LoRA (`lora_config.json`)
  and load them, **or fold them in** with `merge_delta.py` → after merging the model
  is **100% stock architecture, no framework patches required**.
- The **`dk1_cartesian` embodiment is `domain_id = 26`**, an *existing* row of the base
  `num_embodiment_domains = 32` embedding — no new params. To use it, just pass
  `domain_id = 26` with the 20-D action layout.
- The training **modes** (`policy` / `causal_policy` / `forward_dynamics` /
  `inverse_dynamics`) are **input-masking recipes, not model features** — the net is
  bidirectional gen-attention, so e.g. `causal_policy` just means "give past frames +
  an RTC action prefix." Any user can run them; they need the masking logic, not special weights.

## How to use

```bash
# Stock, patch-free model (recommended): fold the delta into the base.
python merge_delta.py \
    --base  /path/to/Cosmos3-Nano-dcp/model \
    --delta cosmos3-dk1-cartesian-delta.safetensors \
    --out   /path/to/Cosmos3-dk1-cartesian-merged/model
```

For DK-1 cartesian closed-loop control, the action convention is:
- **20-D** bimanual = per arm `[pos_delta(3), rot6d_delta(6), gripper(1)]`, left then right.
- **Single-step** (`backward_framewise`) SE(3) deltas `ΔT_t = T_{t-1}⁻¹ T_t` of the
  end-effector (**flange** frame, OpenCV convention: z=approach/front, x=right), 6D rotation
  (Zhou et al. 2019); gripper is the **absolute** state (not a delta).
- Quantile-normalized with `dk1_action_normalization_cartesian.json` (grippers forced (0,1)→(−1,1)).
- EE poses via FK over the DK-1 dual-arm URDF; closed-loop needs IK back to joints.

## Training recipe (summary)

- Base: Cosmos3-Nano (MoT: frozen Qwen3-VL-8B reasoner + diffusion gen expert).
- Gen attention **full-FT** + gen MLP **LoRA r16** (path-qualified to the gen expert only) + action I/O **full-FT**.
- Multi-mode SFT (policy / causal_policy / forward_dynamics / inverse_dynamics), RTC, JSON caption metadata + CFG dropout.
- 21-source DK-1 datamix, 480p, chunk_length 32, `action_loss_weight = 2`, ~0.18 epoch at 25k steps.
- Full project + training code: https://github.com/andreaskoepf/cosmos3-dk1

## License
OpenMDW-1.1 (inherits from Cosmos3-Nano). The DK-1 URDF used for FK is Apache-2.0.