Published 2 days ago

Quantization Space Utilization Rate (QSUR): A Novel Post-Training Quantization Method Designed to Enhance the Efficiency of Large Language Models (LLMs)

Summary by MarkTechPost

Post-training quantization (PTQ) focuses on reducing the size and improving the speed of large language models (LLMs) to make them more practical for real-world use. Such models require large data volumes, but strongly skewed and highly heterogeneous data distribution during quantization presents considerable difficulties. This would inevitably expand the quantization range, making it, in most values, a less accurate expression and reducing gene…

Think freely.Subscribe and get full access to Ground NewsSubscriptions start at $9.99/year

Stories disproportionately reported by the Left or the Right

Coverage Details

Total News Sources0

Leaning Left0Leaning Right0Center0Last Updated1 day agoBias Distribution

No sources with tracked biases.

Bias Distribution

There is no tracked Bias information for the sources covering this story.

Factuality

To view factuality data please Upgrade to Premium

Ownership

To view ownership data please Upgrade to Vantage

Sources are mostly out of (0)

Quantization Space Utilization Rate (QSUR): A Novel Post-Training Quantization Method Designed to Enhance the Efficiency of Large Language Models (LLMs)

Coverage Details

Bias Distribution

Ownership

Similar News Topics

Similar News Topics