LoRA, AdaLoRA, QLoRA, a review of the principle of efficient fine-tuning technology for large model parameters - Code World

LoRA, AdaLoRA, QLoRA, a review of the principle of efficient fine-tuning technology for large model parameters

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Origin blog.csdn.net/qq_27590277/article/details/131199017

LoRA, AdaLoRA, QLoRA, a review of the principle of efficient fine-tuning technology for large model parameters

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

Simple understanding of LoRA (Low-Rank Adaptation) in efficient fine-tuning of large model parameters

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

LLMs: LLaMA Efficient Tuning (an efficient tool that can efficiently fine-tune [full parameters/LoRA/QLoRA] mainstream large models [ChatGLM2/LLaMA2/Baichuan, etc.] [pre-training + instruction supervision fine-tuning +

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Generative AI New World | Overview of the principles of efficient fine-tuning and quantification of large model parameters

LORA large model accelerates fine-tuning and training algorithms

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

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

【LLM】Financial large model scene and large model Lora fine-tuning practice

Practical application of large models 10 - Detailed explanation of large model domain knowledge and parameter efficient fine-tuning (PEFT) technology, and use PEFT to train your own large models

[Natural Language Processing] [Large Model] LoRA and BLOOM-LORA implementation codes for fine-tuning large model methods with very low resources

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

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LLM-Project Detailed Explanation-Chinese-LLaMA-AIpaca (1): LLM+LoRa fine-tuning acceleration technology principle and PEFT-based hands-on practice: some thoughts and a complete case of mt0-large+lora

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Simple understanding of LoRA (Low-Rank Adaptation) in efficient fine-tuning of large model parameters

Simple understanding of LoRA (Low-Rank Adaptation) in efficient fine-tuning of large model parameters

Simple understanding of LoRA (Low-Rank Adaptation) in efficient fine-tuning of large model parameters

Stable Diffusion: Fine-tuning the LoRA model with your own dataset

Efficient fine-tuning practice of LLaMA, ChatGLM, BLOOM parameters

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