If you run LLMs locally, these are the settings you need to be aware of.

Huawei’s Computing Systems Lab in Zurich has introduced a new open-source quantization method for large language models (LLMs) aimed at reducing memory demands without sacrificing output quality.

Abstract: Analog-to-digital converters (ADCs) play a critical role in digital signal acquisition across various applications, but their performance is inherently constrained by sampling rates and bit ...

MATLAB PCM System Simulator demonstrating digital signal processing fundamentals. Features sampling, quantization (uniform/μ-law), multiple encoding schemes, and signal reconstruction. Includes ...

Large Language Models (LLMs) have made significant advancements in natural language processing but face challenges due to memory and computational demands. Traditional quantization techniques reduce ...

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

Abstract: Recent research in sampling theory suggests utilizing unlimited sampling with one-bit quantization time-varying threshold (UNO) for bandlimited signals. The UNO framework addresses the ...

Sampling originated from DJ Kool Herc's Merry-Go-Round technique. Over time, the technique evolved and has created hip-hop songs with ties that go back decades. The legal battles with clearing samples ...