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4 changes: 2 additions & 2 deletions README.md
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## Introduction

**Dexbotic** is a VLA (Vision-Language-Action) development toolbox built on the PyTorch framework, designed to provide a unified and efficient solution for embodied intelligence research. It comes with built-in environment configurations for various mainstream VLA models, allowing users to reproduce, fine-tune, and inference cutting-edge VLA algorithms with simple setup.
**Dexbotic** is a VLA (Vision-Language-Action) development toolbox built on the PyTorch framework, designed to provide a unified and efficient solution for embodied intelligence research. It comes with built-in environment configurations for various mainstream VLA models, allowing users to reproduce, fine-tune, and run inference on cutting-edge VLA algorithms with a simple setup.

- **Ready-to-Use VLA Framework**: Centered around VLA models, integrating embodied manipulation and navigation capabilities, supporting multiple cutting-edge algorithms.
- **High-Performance Pre-trained Foundation Models**: For mainstream VLA algorithms such as π0 and CogACT, Dexbotic provides multiple optimized pre-trained models.
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<summary>Q: Coverting RLDS/LeRobot to Dexdata</summary>
<summary>Q: Converting RLDS/LeRobot to Dexdata</summary>

A: We provide a general data conversion guide in [data conversion](docs/Data.md#2-data-conversion). An example of Lerobot data conversion can be found in [convert_lerobot_to_dexdata](script/convert_data/convert_lerobot_to_dexdata.py), and an example for RLDS data conversion is available in [convert_rlds_to_dexdata](script/convert_data/convert_rlds_to_dexdata.py).
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