Weight Quantization
A technique that converts neural network weights from high-precision floating-point numbers to lower-precision representations such as INT8, FP8, and INT4. It reduces memory footprint and computational load, thereby accelerating inference.
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Common inference optimization methods in the industry include weight quantization (INT8/FP8/INT4), KV Cache reuse and paging, continuous batching, speculative decoding, and others.
Engineering pathways for compressing and deploying models onto space hardware typically include knowledge distillation, weight quantization, and task-specific pruning.
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Common inference optimization methods in the industry include weight quantization (INT8/FP8/INT4), KV Cache reuse and paging, continuous batching, speculative decoding, and others.
50%UnverifiedEngineering pathways for compressing and deploying models onto space hardware typically include knowledge distillation, weight quantization, and task-specific pruning.
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