Text-to-Image
Diffusers
Safetensors
stable-diffusion-xl
stable-diffusion-xl-diffusers
controlnet
diffusers-training
Instructions to use Acopa/sdxl_controlnet_deep_fash_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Acopa/sdxl_controlnet_deep_fash_test with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Acopa/sdxl_controlnet_deep_fash_test") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from Acopa/sdxl_controlnet_deep_fash_test: direct link, hf CLI and curl.
- Browser
- Download file 10 GB
-
https://huggingface.co/Acopa/sdxl_controlnet_deep_fash_test/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://Acopa/sdxl_controlnet_deep_fash_test/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Acopa/sdxl_controlnet_deep_fash_test/resolve/main/checkpoint-2000/optimizer.bin
10 GB
- Xet hash:
- 9bfe4c58240220cc8579bb48e6592371b8dffae6e00b7bf6218a22d1a2afd2f5
- Size of remote file:
- 10 GB
- SHA256:
- f164f3f0a89290021b14029d2cf6fcf84b4de8f21db735a698f452b51572ec4c
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