对llama使用lora:github.com/Lightning-AI 另外,也感谢苏神的博客科学空间 解答了我很多困惑～ 1 大模型微调技术原理概述 我们知道自ChatGPT爆火以来,国内外科技公司都开始重兵部署在LLM上,比如Meta的Llama、国内的ChatGLM 和Qwen等,这些模型动辄几十B(Billion)的参数量,以70B的模型为例,假设模型参数都以FP16数据...
hiyouga/LLaMA-Factory: Unified Efficient Fine-Tuning of 100+ LLMs (ACL 2024)来自LLaMA-Factory的...
本文以LoRA: Low-Rank Adaptation of Large Language Models为例，介绍大模型微调技术。首先，我们了解大模型微调的背景和原理。由于大模型参数量巨大，如70B参数的模型，仅以FP16数据类型存储，weight数据就需要130GB显存。因此，大模型微调技术旨在通过微调少量参数实现模型迁移，LoRA便是当前主流的微调技术...
Thanks to QLoRA, fine-tuning large language models (LLMs) has become more accessible and efficient. With QLoRA, you can fine-tune a massive 65 billion parameter model on a single GPU with just 48GB of memory, without compromising on quality. This is equivalent to the full 16-bit training...
球球了再中一次吧QAQ创建的收藏夹llm内容:[LLMs 实践] 02 LoRA(Low Rank Adaption)基本原理与基本概念,fine-tune 大语言模型,如果您对当前收藏夹内容感兴趣点击“收藏”可转入个人收藏夹方便浏览
costs of traditional fine-tuning methods and the goal of improving performance,this study investigate the application of low-rank adaptation (LoRA) for fine-tuning BERT models to Portuguese Legal Named Entity Recognition (NER) and the integration of Large Language Models (LLMs) in an ensemble ...
Llama3是Meta开发的最新一代大型语言模型(LLM)。这些模型是在15万亿token的广泛数据集上训练的(相比之下,Llama2的训练数据集为2万亿token)。发布了两种模型尺寸:一个700亿参数的模型和一个更小的80亿参数的模型。700亿参数的模型已经展示了令人印象深刻的性能,在MMLU基准测试中得分为82,在HumanEval基准测试中得分为...
[LLMs 实践] 03 LoRA fine-tune 大语言模型(peft、bloom 7b) 1.3万播放 【研1基本功 (真的很简单)LoRA 低秩微调】大模型微调基本方法1 —— bonus "Focal loss" 3.8万播放 【精校】“让我们重现GPT-2(1.24亿参数)!”AI大神Andrej Karpathy最新4小时经典教程 【中英】 4.9万播放 【珍藏】从头开始用代码...
!CUDA_VISIBLE_DEVICES=1 /media/zr/Data/Code/ChatGLM3/venv/bin/python3 finetune_hf.py data/AdvertiseGen_fix /media/zr/Data/Models/LLM/chatglm3-6b configs/lora.yaml Loading checkpoint shards: 100%|██████████████████| 7/7 [01:33<00:00, 13.38s/it] --> Model ...
‘### Instruction:\nUse the provided input to create an instruction that could have been used to generate the response with an LLM.\n\n### Input:\nThe best way to cook food is over a fire. You’ll need to build a fire and light it first, and then heat food in a pot on top...