LLM FAQ (Fine-tuning section) - Code World

LLM FAQ (Fine-tuning section)

Enterprise 2023-12-17 15:17:36 views: null

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Origin blog.csdn.net/YuqingF/article/details/134408441

LLM FAQ (Fine-tuning section)

LLM FAQ (LangChain section)

Fine-tuning LLM with a single GPU

Summary of LLM model fine-tuning methods

LLM - SFT workflow fine-tuning workflow

【LLM】Prompt tuning large model fine-tuning practice

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

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

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

LLM: New paradigm of Prompt-Tuning/Instruction-tuning fine-tuning

[LLM] self-instruct construction instruction fine-tuning data set

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

LangChain and LangSmith: A dual strategy for building and fine-tuning smart applications that support LLM

【CS324】LLM (large model capabilities, data, architecture, distributed training, fine-tuning, etc.)

LLM fine-tuning (3) | Analysis of RLHF + Reward Model + PPO technology in large models

Common techniques in LLM large language model training: fine-tuning and embedding

LLM-Large Model Training-Step (3): Instruction fine-tuning [Superviser Fine-Tuning] [Chinese instruction corpus] [Training method is the same as unsupervised learning] [Instruction corpus style: instruction+input+output]

LoRA fine-tuning

PEFT fine-tuning

How to reduce model cost? Platypus: Fast, cheap and powerful LLM that beats the competition with only one GPU and 5 hours of LLaMA2 fine-tuning

OpenAI bilingual documentation reference Fine-tuning fine-tuning

Lightweight fine-tuning Parameter-Efficient Fine-Tuning

LLMs instruction fine-tuning Instruction fine-tuning

Fine-tuning of sd and fine-tuning of lora in diffusers

Preprocessing for model fine-tuning

SFT supervised fine-tuning

EMA training fine-tuning

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

Java Interview FAQ - thread section (with answers)

Large model LLM-fine-tuning experience sharing & summary

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