On the overview of efficient fine-tuning of large models: Adapter Tuning, AdaMix, PET, Prefix-Tuning, Prompt Tuning, P-tuning, P-tuning v2 - Code World

On the overview of efficient fine-tuning of large models: Adapter Tuning, AdaMix, PET, Prefix-Tuning, Prompt Tuning, P-tuning, P-tuning v2

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Origin blog.csdn.net/qq_56591814/article/details/131293940

On the overview of efficient fine-tuning of large models: Adapter Tuning, AdaMix, PET, Prefix-Tuning, Prompt Tuning, P-tuning, P-tuning v2

Summary of fine-tuning methods for large models: LoRA, Adapter, Prefix-tuning, P-tuning, Prompt-tuning

Overview of the principles of efficient fine-tuning technology for large model parameters (2) - BitFit, Prefix Tuning, Prompt Tuning

Popular understanding of major fine-tuning methods for large models: from Prefix Tuning, P-Tuning V1/V2 to LoRA, QLoRA

P-Tuning v2: Prompt optimization equal to fine-tuning performance

К обзору эффективной тонкой настройки больших моделей: Adapter Tuning, AdaMix, PET, Prefix-Tuning, Prompt Tuning, P-tuning, P-tuning v2

Efficient fine-tuning technology for large models

P-tuning paper overview

Summary of three fine-tuning techniques for pre-training large language models: fine-tuning, parameter-efficient fine-tuning and prompt-tuning

P-Tuning v2 paper overview

Zum Überblick über effizientes Feintuning großer Modelle: Adapter Tuning, AdaMix, PET, Prefix-Tuning, Prompt Tuning, P-Tuning, P-Tuning v2

Paper Notes P-Tuning v2 Suggestive optimization equal to fine-tuning performance

[Instruction fine-tuning of LLM series] Long story short, "Prompt" for instruction fine-tuning of large models

Efficient fine-tuning of large models - introduction to the PEFT framework

Take you hand in hand to realize the P-Tuning fine-tuning of ChatGLM2-6B

ChatGLM2-6B fine-tuning practice based on P-Tuning v2 | JD Cloud technical team

Under the overview of efficient fine-tuning of large models: DiffPruning, BitFit, LoRa, AdaLoRA, MAM Adapters, UniPELT

The secret weapon for efficient development of large models: MindSpore PET, a low-parameter fine-tuning kit for large models

【LLM】Prompt tuning large model fine-tuning practice

A Survey of Fine-tuning Methods for Large Models

Summary of fine-tuning techniques for large models

【ChatGLM】ChatGLM fine-tuning of large models

대형 모델의 효율적인 미세 조정 개요: Adapter Tuning, AdaMix, PET, Prefix-Tuning, Prompt Tuning, P-tuning, P-tuning v2

Sur la vue d'ensemble du réglage fin efficace des grands modèles : Adapter Tuning, AdaMix, PET, Prefix-Tuning, Prompt Tuning, P-tuning, P-tuning v2

[Paper Reading Notes 75] P-Tuning v2

Lightweight fine-tuning Parameter-Efficient Fine-Tuning

Large language model fine-tuning and PEFT efficient fine-tuning

Large model-DeltaTuning-incremental 03: Prompt-Tuning (P-tuning v1) [Only add a trainable parameter layer to the input layer]

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

LaVIN—Efficient Instruction Fine-tuning for Multimodal Dialogue Models

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