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SD15-LORA-3DStyle-202405222331-v2



Model Introduction

test-v2

Model Parameters

Base Model Tuner Type Training Parameters
Batch Size Epochs Learning Rate Resolution
SD1.5 LORA 2 100 0.0001 [512, 512]
Data Type Data Space Data Name Data Subset
Dataset zip /mnt/codespace/yinzi/project/scepter/scepter_gitlab_dev/scepter/cache/scepter_ui/datasets/scepter_txt2img_3D_example

Model Performance

Given the input "a boy wearing a jacket," the following image may be generated:

image

Model Usage

Command Line Execution

git clone https://github.com/modelscope/scepter.git
cd scepter
pip install -r requirements/recommended.txt
PYTHONPATH=. python scepter/tools/run_inference.py
  --pretrained_model {this model folder}
  --cfg {lora_cfg} or {sce_cfg} or {text_lora_cfg} or {text_sce_cfg}
  --prompt 'a boy wearing a jacket'
  --save_folder 'inference'
  • Running after Installing Scepter (Recommended)
pip install scepter
python -m scepter/tools/run_inference.py
  --pretrained_model {this model folder}
  --cfg {lora_cfg} or {sce_cfg} or {text_lora_cfg} or {text_sce_cfg}
  --prompt 'a boy wearing a jacket'
  --save_folder 'inference'

Running with Scepter Studio

pip install scepter
# Launch Scepter Studio
python -m scepter.tools.webui
  • Refer to the following guides for model usage.

(video url)

Model Reference

If you wish to use this model for your own purposes, please cite it as follows.

@misc{SD15-LORA-3DStyle-202405222331-v2,
    title = {SD15-LORA-3DStyle-202405222331-v2, https://huggingface.co/jiangzeyinzi/SD15-LORA-3DStyle-202405222331-v2},
    author = {jiangzeyinzi},
    year = {2024}
}

This model was trained using Scepter Studio; Scepter is an algorithm framework and toolbox developed by the Alibaba Tongyi Wanxiang Team. It provides a suite of tools and models for image generation, editing, fine-tuning, data processing, and more. If you find our work beneficial for your research, please cite as follows.

@misc{scepter,
    title = {SCEPTER, https://github.com/modelscope/scepter},
    author = {SCEPTER},
    year = {2023}
}
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