Efficient-Large-Model / Long-WAM-RoboTwin2.0-IDM

huggingface.co
Total runs: 31
24-hour runs: 0
7-day runs: 31
30-day runs: 31
Model's Last Updated: October 06 2026
robotics

Introduction of Long-WAM-RoboTwin2.0-IDM

Model Details of Long-WAM-RoboTwin2.0-IDM

Long-WAM RoboTwin2.0-IDM

Long-WAM policy weights for RoboTwin2.0. IDM predicts actions after generating future-video latents.

Download
hf download Efficient-Large-Model/Long-WAM-RoboTwin2.0-IDM --local-dir ./weights/Long-WAM-RoboTwin2.0-IDM
Inference

Load model.pt with the matching Long-WAM runtime, using config.yaml and the supplied dataset_stats.json for preprocessing and normalization.

P48 context uses 48 past control steps plus the current observation, encoded into four clean latent frames.

Generate two future-video latents using 4 steps (imagination sigma 0.9), then predict a 32-step action chunk using 10 action steps. Replan every 24 executed actions. Reset history at the start of each episode.

The matching inference runtime and base-model VAE/text assets are required separately. This release contains weights and inference settings only; optimizer states and training artifacts are not included.

Runs of Efficient-Large-Model Long-WAM-RoboTwin2.0-IDM on huggingface.co

31
Total runs
0
24-hour runs
12
3-day runs
31
7-day runs
31
30-day runs

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https://huggingface.co/Efficient-Large-Model/Long-WAM-RoboTwin2.0-IDM

Long-WAM-RoboTwin2.0-IDM install

Long-WAM-RoboTwin2.0-IDM is an open source model from GitHub that offers a free installation service, and any user can find Long-WAM-RoboTwin2.0-IDM on GitHub to install. At the same time, huggingface.co provides the effect of Long-WAM-RoboTwin2.0-IDM install, users can directly use Long-WAM-RoboTwin2.0-IDM installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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https://huggingface.co/Efficient-Large-Model/Long-WAM-RoboTwin2.0-IDM

Url of Long-WAM-RoboTwin2.0-IDM

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