Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation
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VinRobotics - Edge AI & Model Optimization
We optimize and deploy LLMs, ASR, VLM and VLA (Vision-Language-Action) models on real-world systems.
Featured Projects
vla.cpp Native C++ inference runtime for Vision-Language-Action models, built for low-latency robotic deployment.
Model Quantization Recipes Practical recipes for quantizing and deploying LLM, ASR, VLM, and VLA models on real-world systems.
What we do
- Optimization: quantization (INT8/INT4/FP8/NVFP4), pruning, distillation, ...
- Deployment: VLLM, TensorRT, ONNX Runtime, edge runtimes
- Systems: real-time pipelines (vision, audio, language, action)
Focus
- Edge devices (Jetson, SoCs)
- Robotics & VLA systems
- Latency, stability, deployability
Philosophy
Optimization = model + runtime + system
models 32
vrfai/foca_libero_s100
Updated
vrfai/foca_libero_s10
4B • Updated
vrfai/pi0_base
4B • Updated
vrfai/foca_dreamgen_libero_s10
4B • Updated • 11
vrfai/foca_dreamgen_libero_s40
4B • Updated • 14
vrfai/vla-adapter-libero-gguf
Robotics • 1B • Updated • 75
vrfai/openvla-oft-libero-gguf
Robotics • 8B • Updated • 80
vrfai/pi05-libero-gguf
Robotics • 3B • Updated • 81
vrfai/gr00tn1d5-libero-object-gguf
Robotics • 2B • Updated • 83
vrfai/gr00tn1d6-libero-gguf
Robotics • 3B • Updated • 94
datasets 0
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