The most efficient approach for a local installation is leveraging Docker containers.
Please follow the instructions listed below to get started.
The setup auto-downloads all needed files (several GBs).
Your resources are automatically evaluated to lock in the premium configuration.
The technique-router-onnx model is designed to optimize dynamic routing decisions in neural network inference pipelines. It leverages the ONNX format to ensure cross‑platform compatibility and seamless integration with existing deep learning frameworks. By employing a lightweight graph representation, the model achieves high throughput while maintaining low memory footprint for edge deployments. The built‑in router module dynamically selects the most efficient sub‑graph for each input, reducing latency and improving overall system scalability. Users can evaluate its performance through the accompanying
| Metric | Value |
|---|---|
| Throughput | 1500 inferences/sec |
| Latency | 2.3 ms |
| Memory | 45 MB |
that compares inference speed, accuracy, and resource usage against baseline routing strategies.
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