Instructions to use ldhnam/deepfashion_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ldhnam/deepfashion_v1 with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("ldhnam/deepfashion_v1") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a5fa7b551227f5d6ef34795a17ee889eef589b10b6876d3194df83daee5b3024
- Size of remote file:
- 1.46 GB
- SHA256:
- 25663664c76041cb800c174e6bbbffaff7f2a64d15676b0240ffd6a55228798b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.