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| title: README |
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| # xrML |
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| *Running quality models on XR devices.* |
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| xrML is a community exploring on-device machine learning for extended reality. Our focus is practical ML for augmented, virtual, and mixed reality experiences. |
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| ## Our focus |
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| - **Efficient inference:** Exploring models and optimization techniques suited to the compute, memory, and power constraints of XR devices. |
| - **On-device deployment:** Investigating how machine learning can run locally within interactive XR applications. |
| - **Practical experimentation:** Exploring the tradeoffs between model quality, responsiveness, and resource use on XR hardware. |
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| ## Supported repositories |
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| We currently support two repositories: |
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| - **[xrBench](https://github.com/Michael-RDev/xrBench):** A benchmarking toolkit for measuring native GPU execution time and checking numerical correctness on XR devices. |
| - **[xrGPU](https://github.com/Michael-RDev/xrGPU):** Native Vulkan compute kernels and runtime components for machine learning workloads on XR hardware. |
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| ## Have an XR device? |
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| Visit **[xrBench](https://github.com/Michael-RDev/xrBench#getting-started)** to review the device requirements and get started with benchmarking. |
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| ## Follow our progress |
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| Follow xrML on Hugging Face for updates on machine learning for XR devices. |
