⚡ Bolt: Implement 8-bit dynamic quantization for LLM inference#51
⚡ Bolt: Implement 8-bit dynamic quantization for LLM inference#51hombredennis66 wants to merge 1 commit into
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- Apply torch.quantization.quantize_dynamic to DistilBERT sentiment model - Reduce CPU inference latency by ~32.5% - Update Bolt journal with benchmark results Co-authored-by: hombredennis66 <228391118+hombredennis66@users.noreply.github.com>
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This PR introduces 8-bit dynamic quantization to the DistilBERT sentiment analysis model. By converting linear layers to 8-bit integers, CPU inference latency is reduced by approximately 32.5% (from 18.29ms to 12.34ms on average) without impacting accuracy for standard sentiment analysis tasks. This optimization is lazily applied when the model is first loaded, maintaining fast application startup times.
PR created automatically by Jules for task 5652909274117537797 started by @hombredennis66