Whisper Speech Models Shrink 75% Without Losing Accuracy
Researchers analyzed Whisper speech models, reducing size by up to 75% with minimal accuracy loss using post-training quantization & quantization-aware training. Different techniques work better for different model sizes.
This is a Plain English Papers summary of a research paper called Whisper Speech Models Shrink 75% Without Losing Accuracy in Groundbreaking Quantization Study. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter. Overview Researchers analyzed different quantization methods for OpenAI's Whisper speech recognition models 8-bit and 4-bit quantization techniques were tested across multiple Whisper model sizes Post-training quantization (PTQ) and quantization-aware training (QAT) approaches were compared Findings show model size reduction up to 75% w...