Downloads · 30 days
4
2% of all-time downloads
wam_3latin_joint_mildrot
hmkang/wam_3latin_joint_mildrot
wam_3latin_joint_mildrot is a robotics model from hmkang. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for wan2.2. The card lists the license as apache-2.0.
Wan2.2-TI2V-5B (diffusers) video DiT + DiT-B action head trained jointly on RoboCasa kitchen with the base recipe (effective batch 64: 4 GPU × per-device 8 × grad-accum 2, fm shift 5.0, bell time-weight, EMA warmup on…
All-time downloads
229
Public
Repo size
130 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors130 GB · 100%
At a glance
- Task
- Robotics
- Library
- wan2.2
- License
- apache-2.0
- Access
- Public
- Created
- Sep 7, 2026
- Updated
- Sep 8, 2026
- SHA
- c09d9dee
Model card
From the Hugging Face model README
WAM_DIT4DIT — 3-latin JOINT (video + action), mild + rotate augmentation, RoboCasa kitchen
Wan2.2-TI2V-5B (diffusers) video DiT + DiT-B action head trained jointly on RoboCasa kitchen with the base recipe (effective batch 64: 4 GPU × per-device 8 × grad-accum 2, fm shift 5.0, bell time-weight, EMA warmup on video + action head, 4-knob A joint setup).
Geometry: 3-latin history — nin=17 / nout=33, frame-downsample 2 (hist 9 → 3 cond latent
- 4 future latent). Image augmentation: mild color/crop jitter + rotation ±5° on all views
(
WAM_IMAGE_AUG=1 WAM_IMAGE_AUG_STRONGER=0 WAM_IMAGE_AUG_MILD_ROTATE=1).
| folder | steps |
|---|---|
checkpoint-<step> | every 20k (80k first) |
Weights (*.safetensors) + config.json + processor / experiment config only; optimizer state and
training_args.bin are not included. Training code: https://github.com/HEMMO0208/wam
(gr00t/model/wam_dit4dit/image_augmentations.py, launcher finetune_wam_dit4dit_robocasa_kitchen_DiT4DiTjoint_wan22.sh).
- Task
- Robotics
- Library
- wan2.2
- License
- apache-2.0
- Created
- Sep 7, 2026
- Updated
- Sep 8, 2026