Instructions to use Abhi5ingh/ControlnetDresscode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Abhi5ingh/ControlnetDresscode with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Abhi5ingh/ControlnetDresscode") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 964 Bytes
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---
license: creativeml-openrail-m
base_model: runwayml/stable-diffusion-v1-5
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- controlnet
inference: true
---
# controlnet-Abhi5ingh/model_dresscode
Have a design in your mind and would love to visualize it? Try my Fashion Generation model available as a playground to test on a hugging face space : https://huggingface.co/spaces/Abhi5ingh/fashionsd
Research Paper: https://arxiv.org/abs/2404.18591
These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with a new type of conditioning on sketch and text.
You can find the results and the validation inference below:
Results:

prompt: hem shoulder top in navy blue

prompt: beautiful floral gown

prompt: one-shoulder textured dress one long draping sleeve one sleeved mini purple evening dress

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