Instructions to use JayCao99/dit-diffusion-rm65b-cns-v0.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use JayCao99/dit-diffusion-rm65b-cns-v0.0 with LeRobot:
# 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
Multi-Task DiT (diffusion)
LeRobot policy checkpoints uploaded by goal_gen/upload_hf_checkpoints.sh.
Each subfolder contains the deployment-ready pretrained_model/ payload
(model.safetensors + config.json + pre/postprocessor + train_config.json).
| Subfolder | Train step | Final train loss |
|---|---|---|
checkpoint-050000 |
50,000 | — |
Usage
from huggingface_hub import snapshot_download
ckpt_dir = snapshot_download(
"JayCao99/dit-diffusion-rm65b-cns-v0.0",
allow_patterns="checkpoint-050000/*",
)
# Then load with the appropriate LeRobot policy class, e.g.:
# from lerobot.policies.multi_task_dit import MultiTaskDiTPolicy
# policy = MultiTaskDiTPolicy.from_pretrained(f"{ckpt_dir}/checkpoint-050000")