Prefix-Tuning论文解读 - 代码天地

Prefix-Tuning论文解读

企业开发 2023-06-19 18:09:45 阅读次数: 0

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转载自blog.csdn.net/Zosse/article/details/130955632

Prefix-Tuning论文解读

Prefix-Tuning 论文概述

Prefix Tuning论文解读

论文笔记 Prefix-Tuning: Optimizing Continuous Prompts for Generation》

【论文笔记】Prefix-Tuning: Optimizing Continuous Prompts for Generation

[论文阅读73]Prefix-Tuning：Optimizing Continuous Prompts for Generation

Prefix-Tuning: Optimizing Continuous Prompts for Generation

【论文精读ACL_2021】Prefix-Tuning: Optimizing Continuous Prompts for Generation

【NLP经典论文精读】Prefix-Tuning: Optimizing Continuous Prompts for Generation

[文献阅读]——Prefix-Tuning: Optimizing Continuous Prompts for Generation

HuggingFace学习笔记--Prompt-Tuning、P-Tuning和Prefix-Tuning高效微调

大模型微调方法总结：LoRA、Adapter、Prefix-tuning、P-tuning、Prompt-tuning

Prompt-Tuning、Instruction-Tuning、prefix tuning的区别；Instruction-Tuning（指令调优），和Prefix-Tuning（前缀调优）相关的例子

大模型微调（finetune）方法总结-LoRA,Adapter,Prefix-tuning，P-tuning，Prompt-tuning

大模型高效微调综述上：Adapter Tuning、AdaMix、PET、Prefix-Tuning、Prompt Tuning、P-tuning、P-tuning v2

Prefix-tuning、Adapter、LLaMA-Adapter的流程图与伪代码实现

【LLM微调范式1】Prefix-Tuning: Optimizing Continuous Prompts for Generation

大模型-微调技术：统一框架（统一Adapter-Tuning、Prefix-Tuning、LoRA）【冻结大模型参数，微调新插入的参数层】

Prefix Tuning：详细解读Optimizing Continuous Prompts for Generation

论文解读：P-Tuning v2: Prompt Tuning Can BeComparable to Fine-tuning Universally Across Scales and Tasks

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-into Attention论文解读

多模态大语言模型 LlaVA 论文解读：Visual Instruction Tuning

论文解读：PRINCE: Prefix-Masked Decoding for Knowledge Enhanced Sequence-to-Sequence Pre-Training

大模型高效参数微调技术（Prompt-Tuning、Prefix Tuning、P-Tuning、LoRA...）

P-tuning论文概述

基于prefix tuning + Bert的标题党分类器

大模型参数高效微调技术原理综述（二）-BitFit、Prefix Tuning、Prompt Tuning

大模型参数高效微调技术原理综述（三）-Prefix Tuning

Adapter Tuning：详细解读Parameter-Efficient Transfer Learning for NLP

DCGAN 论文简单解读

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