Add model card for AnyPos

README.md

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+---
+pipeline_tag: robotics
+---
+
+# AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation
+
+AnyPos (also referred to as **Vidar** in the codebase) is a unified pipeline that integrates large-scale automated task-agnostic exploration with robust embodiment modeling through inverse dynamics learning. By focusing on exploring all feasible actions of the embodiment, AnyPos learns embodiment dynamics directly from task-agnostic action data and decouples them from high-level policy learning.
+
+- **Paper:** [AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation](https://huggingface.co/papers/2507.12768)
+- **Project Page:** [https://embodiedfoundation.github.io/vidar_anypos](https://embodiedfoundation.github.io/vidar_anypos)
+- **Repository:** [https://github.com/yaofeng1998/Vidar](https://github.com/yaofeng1998/Vidar)
+
+## Introduction
+
+AnyPos generates diverse yet safe trajectories at scale, then learns embodiment representations by decoupling arm and end-effector motions. It employs a direction-aware decoder to stabilize predictions under distribution shift, allowing it to be coupled with diverse high-level policy models. The system has demonstrated significant success rate improvements across tasks such as operating a microwave, folding clothes, and watering plants.
+
+## Environment Setup
+
+The code has been tested with CUDA 12.4.
+
+### 1. Create and Activate Conda Environment
+```bash
+conda create -n vidar python==3.11.9
+conda activate vidar
+```
+
+### 2. Install Dependencies
+```bash
+conda install pytorch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0 pytorch-cuda=12.4 -c pytorch -c nvidia
+python -m pip install -r requirements.txt
+python -m pip install ninja
+python -m pip install git+https://github.com/Dao-AILab/flash-attention.git@v2.6.3
+python -m pip install xfuser==0.4.0
+```
+
+## Usage
+
+The AnyPos pipeline consists of a Video Diffusion Model and a Masked Inverse Dynamic Model.
+
+### Video Diffusion Model (Vidar) Inference
+To generate a video based on an initial frame and a text instruction:
+```bash
+scripts/vm/sample.sh
+```
+
+### Masked Inverse Dynamic Model Inference
+To evaluate the inverse dynamic model:
+```bash
+scripts/idm/eval.sh
+```
+
+## Citation
+
+```bibtex
+@article{anypos2025,
+  title={AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation},
+  author={Yao, Feng and others},
+  journal={arXiv preprint arXiv:2507.12768},
+  year={2025}
+}
+```