HuggingFace study notes--BitFit efficient fine-tuning - Code World

HuggingFace study notes--BitFit efficient fine-tuning

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Origin blog.csdn.net/weixin_43863869/article/details/134759033

HuggingFace study notes--BitFit efficient fine-tuning

pytorch study notes (39): Fine-Tuning

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

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

Lightweight fine-tuning Parameter-Efficient Fine-Tuning

Efficient fine-tuning technology for large models

LoRA fine-tuning comes from huggingface official hugging face

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

LaVIN—Efficient Instruction Fine-tuning for Multimodal Dialogue Models

[NLP] LLM efficient fine-tuning (PEFT)--LoRA

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

QLoRA: Efficient fine-tuning strategies and practices for quantitative LLM

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

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

NLP (sixty-six) uses the Trainer in HuggingFace for BERT model fine-tuning

Detailed notes on fine-tuning Llama 2 using QLoRA

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

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

[Natural Language Processing] Efficient fine-tuning of large models: PEFT use cases

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

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

LLMs Parameter efficient fine-tuning PEFT techniques 2: Soft prompts

On the overview of efficient fine-tuning of large models: 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

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

Meta proposes a new parameter efficient fine-tuning scheme, only one RNN is needed, and the GPU usage of the Transformer model is reduced by 84%!

LLMs PEFT技术1：LoRA Parameter efficient fine-tuning PEFT techniques 1: LoRA Low rank Adaptation

HuggingFace study notes--Using API to implement simple NLP tasks

Study notes, "McKinsey elite efficient Reading"

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