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1. 环境配置

# 请运行这里安装所需要的依赖环境！！
!pip install "paddlenlp>=2.5.2" safetensors "ppdiffusers>=0.11.1" --user

Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
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[1m[[0m[34;49mnotice[0m[1;39;49m][0m[39;49m A new release of pip available: [0m[31;49m22.1.2[0m[39;49m -> [0m[32;49m23.0.1[0m
[1m[[0m[34;49mnotice[0m[1;39;49m][0m[39;49m To update, run: [0m[32;49mpip install --upgrade pip[0m

2. huggingFace 登录

!git config --global credential.helper store
from huggingface_hub import login
login('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')

Token will not been saved to git credential helper. Pass `add_to_git_credential=True` if you want to set the git credential as well.
Token is valid.
Your token has been saved to /home/aistudio/.cache/huggingface/token
Login successful

训练模型

!python train_dreambooth_lora.py \
  --pretrained_model_name_or_path="runwayml/stable-diffusion-v1-5"  \
  --instance_data_dir="./data" \
  --output_dir="lora_outputs" \
  --instance_prompt="a photo of delicious fried food" \
  --resolution=512 \
  --train_batch_size=2 \
  --gradient_accumulation_steps=1 \
  --checkpointing_steps=100 \
  --learning_rate=1e-4 \
  --lr_scheduler="constant" \
  --lr_warmup_steps=0 \
  --max_train_steps=500 \
  --seed=0 \
  --lora_rank=4 \
  --push_to_hub=False \
  --validation_prompt="a photo of fried food on the plate" \
  --validation_steps=100 \
  --num_validation_images=2

W0329 21:20:43.059805  2742 gpu_resources.cc:85] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 11.2, Runtime API Version: 11.2
W0329 21:20:43.075484  2742 gpu_resources.cc:115] device: 0, cuDNN Version: 8.2.
正在下载模型权重，请耐心等待。。。。。。。。。。
[33m[2023-03-29 21:20:46,010] [ WARNING][0m - You are using a model of type clip_text_model to instantiate a model of type . This is not supported for all configurations of models and can yield errors.[0m
Train Steps:  20%|█▌      | 100/500 [00:53<03:32,  1.88it/s, epoch=0016, lr=0.0001, step_loss=0.241]
 Saved lora weights to lora_outputs/checkpoint-100
Train Steps:  40%|███▏    | 200/500 [01:58<02:38,  1.89it/s, epoch=0033, lr=0.0001, step_loss=0.174]
 Saved lora weights to lora_outputs/checkpoint-200
Train Steps:  60%|████▊   | 300/500 [03:02<01:34,  2.12it/s, epoch=0049, lr=0.0001, step_loss=0.151]
 Saved lora weights to lora_outputs/checkpoint-300
Train Steps:  80%|█████▌ | 400/500 [04:07<00:53,  1.87it/s, epoch=0066, lr=0.0001, step_loss=0.0207]
 Saved lora weights to lora_outputs/checkpoint-400
Train Steps: 100%|████████| 500/500 [05:12<00:00,  1.88it/s, epoch=0083, lr=0.0001, step_loss=0.171]
 Saved lora weights to lora_outputs/checkpoint-500
Model weights saved in lora_outputs/paddle_lora_weights.pdparams
Train Steps: 100%|████████| 500/500 [05:49<00:00,  1.43it/s, epoch=0083, lr=0.0001, step_loss=0.171]
[0m

4. 权重上传

from utils import upload_lora_folder
# 使用前请确保已经登录了huggingface hub！
upload_dir                    = "lora_outputs"                      # 我们需要上传的文件夹目录
repo_name                     = "lora_fried_food"                     # 我们需要上传的repo名称
pretrained_model_name_or_path = "runwayml/stable-diffusion-v1-5"    # 训练该模型所使用的基础模型
prompt                        = "a photo of delicious fried food"    # 搭配该权重需要使用的Prompt文本

upload_lora_folder(
    upload_dir=upload_dir,
    repo_name=repo_name,
    pretrained_model_name_or_path=pretrained_model_name_or_path,
    prompt=prompt, 
)

paddle_lora_weights.pdparams:   0%|          | 0.00/3.23M [00:00<?, ?B/s]



Upload 1 LFS files:   0%|          | 0/1 [00:00<?, ?it/s]


模型权重已经上传到了， https://huggingface.co/LianDanShi/lora_fried_food/tree/main/

此文章为搬运
原项目链接