Instructions to use periphanes/cosmos3-gr1-difforce-statefix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use periphanes/cosmos3-gr1-difforce-statefix 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
- Notebooks
- Google Colab
- Kaggle
Cosmos3-Nano GR-1 — Diffusion-Forcing + StateFix checkpoints
PyTorch Distributed Checkpoint (DCP) checkpoints from joint WM + Action SFT of
NVIDIA Cosmos3-Nano (Omni-MoT World Foundation Model) on GR-1, using a causal
diffusion-forcing schedule with a fixed proprio-state prefix ("statefix").
Two long-horizon variants are provided, each at iteration 20,000 (the latest checkpoint):
| Subfolder | Horizon | chunk_length | latent_t | Training |
|---|---|---|---|---|
h65/ |
65-frame | 64 | 17 | 8×B200, FSDP, 45,056-token packing |
h129/ |
129-frame | 128 | 33 | 8×B200, FSDP, 45,056-token packing |
Layout
Each subfolder mirrors the framework's checkpoint layout (full DCP — model + optimizer + scheduler + trainer state), so it can be resumed or evaluated directly:
<variant>/
config.yaml, config.pkl, job_env.yaml, launch_info.yaml
checkpoints/
latest_checkpoint.txt
iter_000020000/
model/ # FSDP-sharded DCP (.distcp shards + .metadata)
optim/ # optimizer state (enables training resume)
scheduler/
trainer/
Note: these are sharded DCP checkpoints (
.distcp+.metadata), not consolidatedsafetensors. Load them withtorch.distributed.checkpointvia the Cosmos3 framework, or consolidate to HF format withcosmos_framework.scripts.export_model.
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