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

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

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Origin blog.csdn.net/qq_18555105/article/details/130224392

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

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

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

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

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

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

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

Efficient fine-tuning technology for large models

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

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

LaVIN—Efficient Instruction Fine-tuning for Multimodal Dialogue Models

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

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

Practical tips for fine-tuning large language models with LoRA

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

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 +

LLaMA Open and Efficient Foundation Language Models

LLaMA: Open and Efficient Foundation Language Models

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

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

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

Lightweight fine-tuning Parameter-Efficient Fine-Tuning

Full-parameter fine-tuning of large language models with limited resources

【LLM系列之LlaMA】Llama: Open and Efficient Foundation Language Models

Bloom&LLAMA of large models----SFT (model fine-tuning)

A Survey of Fine-tuning Methods for Large Models

Summary of fine-tuning techniques for large models

【ChatGLM】ChatGLM fine-tuning of large models

The seventh of the large language model - Llama-2 single GPU fine-tuning SFT

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

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