Instructions to use nvidia/Cosmos3-Nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use nvidia/Cosmos3-Nano with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Diffusers
How to use nvidia/Cosmos3-Nano with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nvidia/Cosmos3-Nano", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Cosmos3 AgiBotWorld 29-D action semantics, normalization, and G1 FK/IK mapping
Hi Cosmos / AgiBotWorld team,
I am using nvidia/Cosmos3-Nano through vLLM-Omni with:
domain_name="agibotworld"view_point="concat_view"action_chunk_size=16raw_action_dim=29- 17-frame, 10 FPS concat-view windows
The inverse-dynamics endpoint returns valid action chunks with shape (16, 29). I can also feed each
returned chunk inline through:
extra_params["action"] = action_chunk
extra_params["action_mode"] = "forward_dynamics"
and Cosmos successfully generates a forward-dynamics video rollout.
I am trying to map these actions to an AgiBot G1 Isaac Sim model for IK -> FK validation.
From the published AgiBotWorld action example and returned chunks, the 29-D structure appears to be
grouped approximately as:
0:7 pose-like block: [x, y, z, qw, qx, qy, qz]
7:9 two scalar body/head-like values
9:16 left end-effector pose-like block
16:19 left hand/gripper-like values
19:26 right end-effector pose-like block
26:29 right hand/gripper-like values
Could you clarify the official specification?
- What is the exact meaning and field order of all 29 dimensions?
- Are the pose blocks expressed in the robot base frame, waist frame, torso frame, world frame, or
another frame? - Is there a reference G1 URDF/USD, joint ordering, and an example converting the 29-D action into G1
joint targets or EE IK targets?
For context, I tested a simple rigid transform from the inferred Cosmos EE pose blocks to FK poses from
our G1 simulator. The fit was poor, which suggests either the 29-D values need a domain normalizer, the
assumed fields/frame are wrong, or inverse-dynamics predictions should not be used as paired coordinate-
calibration labels.
Any official schema, normalizer, or reference conversion code would be very helpful. Thanks.