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@@ -61,7 +61,7 @@ variety of hardware - locally and in the cloud.
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- Plain C/C++ implementation without any dependencies
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- Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks
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- AVX, AVX2 and AVX512 support for x86 architectures
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-- 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use
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+- 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use
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- Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP)
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- Vulkan, SYCL, and (partial) OpenCL backend support
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- CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity
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Mirko185