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

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

Enterprise 2023-06-21 20:35:06 views: null

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Origin blog.csdn.net/u013250861/article/details/131255257

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

Large model-DeltaTuning-incremental 03: Prompt-Tuning(P-tuning v1) [입력 레이어에 훈련 가능한 매개변수 레이어만 추가]

Large model-DeltaTuning-incremental 03 : Prompt-Tuning (P-tuning v1) [Ajouter uniquement une couche de paramètres entraînables à la couche d'entrée]

Большая модель-DeltaTuning-incremental 03: Prompt-Tuning (P-tuning v1) [Добавить только слой обучаемых параметров к входному слою]

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

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

Large model-fine-tuning technology: unified framework (unified Adapter-Tuning, Prefix-Tuning, LoRA) [freeze large model parameters, fine-tune the newly inserted parameter layer]

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

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

Modelo grande-DeltaTuning-incremental 03: Prompt-Tuning (P-tuning v1) [Solo agregue una capa de parámetros entrenables a la capa de entrada]

Grande modelo-DeltaTuning-incremental 03: Prompt-Tuning (P-tuning v1) [Adicione apenas uma camada de parâmetro treinável à camada de entrada]

Großes Modell-DeltaTuning-inkrementell 03: Prompt-Tuning (P-Tuning v1) [Füge nur eine trainierbare Parameterebene zur Eingabeebene hinzu]

Add Layer

adding a plurality of input boxes layer.prompt

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

Tensorflow-add_layer (add neural layer)

Pytorch model add, delete, modify network layer

Mask layer only half?

【LLM】Prompt tuning large model fine-tuning practice

Custom add layer

Tensorflow add_layer

[Paper Reading Notes 75] P-Tuning v2

P-Tuning v2 paper overview

Reprinted: Vue add a layer of an intermediate layer --service

layer

Batch Normalization magic if only a model training BN layer would be like

[Pytorch] View the parameter values of a certain layer of the model (self-use)

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

Convolution layer parameter calculation and setting

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

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