Instructions to use knightnemo/robotwin-icl-v3-arx-x5-vam-ti2v5b-openwam-eef-mask-v3-no-ref-train20-100k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Wan2.2
How to use knightnemo/robotwin-icl-v3-arx-x5-vam-ti2v5b-openwam-eef-mask-v3-no-ref-train20-100k with Wan2.2:
# 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
| { | |
| "checkpoint": "step-100000.safetensors", | |
| "local_source": "/cpfs/huangsq/VAM_Learn_from_Human_Video/src/vam/models/train/vam_icl/paired_v3_alltasks_mv_mot_ti2v5b_16g_100k_mask_v3_no_ref_openwam_eef_fastwam_warmstart_0522_1010/step-100000.safetensors", | |
| "checkpoint_size_bytes": 12041705425, | |
| "checkpoint_mtime_utc": "2026-05-24 12:15:27 UTC", | |
| "dataset": "robotwin-icl-paired-v3", | |
| "target_robot": "arx-x5", | |
| "task_split": "train20", | |
| "mask_variant": "v3", | |
| "full_reference_video": false, | |
| "reference_setting": "no_ref", | |
| "action_expert_style": "openwam", | |
| "action_space": "eef", | |
| "proprio_space": "eef", | |
| "action_dim": 16, | |
| "training_steps": 100000, | |
| "training_shape": "2 nodes x 8 GPUs", | |
| "wan_model": "Wan2.2-TI2V-5B", | |
| "backbone_warmstart": "ActionMoT_openwam_linear_interp_Wan22_alphascale_1024hdim.pt", | |
| "wandb_run": "https://wandb.ai/wuji-tech/vam_icl/runs/80vlexr0" | |
| } |