Training Duration: 10,000 steps (resumed from pre-trained foundation).
Final Metrics:
Action Loss: ~0.0044 (High precision motor control).
Latent Loss: ~0.23 (Stable physical imagination).
🚀 How to Use
This repository contains the Transformer weights only. To deploy this model, you must use the LingBot-VA codebase and provide the original VAE and Text Encoder.
Installation & Deployment
For detailed deployment instructions on a fresh PC, please refer to the inference-deployment-guide.md found in the original repository.
Environment: Python 3.10, PyTorch 2.9.0.
Assembly: Download the base robbyant/lingbot-va-base weights.
Injection: Replace the base transformer weights with the ones provided here.
This model uses a Mixture-of-Transformers (MoT) architecture with 5.3 billion parameters. It interleaves video and action tokens in a shared latent space to perform closed-loop world modeling.
