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LingBot-VLA is an open-source Vision-Language-Action (VLA) foundational AI model designed to serve as a general “brain” for real-world robotic manipulation by grounding multimodal perception and language into actionable motions. It has been pretrained on tens of thousands of hours of real robotic interaction data across multiple robot platforms, which enables it to generalize well to diverse morphologies and tasks without needing extensive retraining on each new bot. The model aims to bridge vision, language understanding, and motor control within one unified architecture, making it capable of understanding high-level instructions and generating coherent low-level actions in physical environments. Because LingBot-VLA includes not just the model weights but also a full production-ready codebase with tools for data handling, training, and evaluation, developers can adapt it to custom robots or simulation environments efficiently.
Features
- Vision-Language-Action multimodal foundation model
- Pretrained on large-scale real robotic manipulation datasets
- Cross-robot generalization with minimal retraining
- Includes tools for training, fine-tuning, and evaluation
- Production-ready codebase for deployment in hardware or simulation
- Open-source with community extensibility
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