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相关概念视频

Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

157
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
157
Energy Losses in Transformers01:21

Energy Losses in Transformers

878
In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
878
Three-Winding Transformers01:19

Three-Winding Transformers

232
Three identical single-phase transformers can be configured to form a three-phase transformer connection, which involves high-voltage and low-voltage windings. The high-voltage windings are denoted by capital letters A-B-C, while the low-voltage windings are labeled with lowercase letters a-b-c, representing their respective phases. This notation helps distinguish between the high and low voltage sides of the transformer.
In the per-unit equivalent circuit of a grounded Y-Y three-phase...
232
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

74
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
74
Reducing Line Loss01:18

Reducing Line Loss

154
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
154
Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

436
The practical equivalent circuits of single-phase two-winding transformers exhibit significant deviations from their idealized versions due to the inherent properties of winding resistance and finite core permeability. These properties result in real and reactive power losses, affecting the transformer's performance. Understanding these deviations is crucial for designing more efficient transformers.
In a practical transformer, each winding exhibits resistance and leakage reactance. The...
436

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相关实验视频

Updated: Jul 7, 2025

Author Spotlight: Analgesic Effect of Tuina on Rat Models with Compression of the Dorsal Root Ganglion Pain
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在不进行再培训的情况下,对基于变压器的模型进行块式压缩.

Gaochen Dong1, W Chen2

  • 1TensorChip, Beijing, China.

Neural networks : the official journal of the International Neural Network Society
|December 23, 2023
PubMed
概括
此摘要是机器生成的。

区块式压缩转换器 (BCT) 提供了一种新的方法来压缩大型语言模型而无需重新训练. 这种方法显著减少了计算资源和内存足迹,同时保持了对基准数据集的高准确性.

关键词:
一个区块的区块.压缩 压缩 压缩 压缩没有培训也没有培训.变压器变压器变压器

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科学领域:

  • 人工智能的人工智能
  • 自然语言处理自然语言处理.
  • 机器学习 机器学习

背景情况:

  • 变压器模型 (例如,GPT-3,ChatGPT,GPT-4) 在语言任务中表现出色,但需要大量的计算资源和内存.
  • 当前的压缩技术和层次量子化技术往往会降低模型的准确性,并需要广泛的重新训练.

研究的目的:

  • 为变压器 (BCT) 引入区块式压缩,这是一个无重新培训的框架,用于高效地部署变压器模型.
  • 解决与大型变压器模型相关的计算和内存挑战.

主要方法:

  • BCT在整个变压器架构中采用块式压缩,包括嵌入式,矩阵乘法和其他组件.
  • 这种方法减轻了量子化引起的数据分布转移,从而消除了重新培训的需要.

主要成果:

  • 一个案例研究表明,在使用BCT的高效模型上,压缩高达7.988倍.
  • 对通用语言理解评估 (GLUE) 数据集的评估显示,准确性降低不到0.9%,优于其他方法.

结论:

  • BCT为压缩变压器模型提供了有效的解决方案,而不会导致准确性损失或重新训练.
  • 该框架通过显著减少它们的资源需求,促进了大型语言模型的更容易部署.