Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
diffusers-training
Instructions to use Jieya/model_out_canny_captioned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jieya/model_out_canny_captioned with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Jieya/model_out_canny_captioned") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from Jieya/model_out_canny_captioned: direct link, hf CLI and curl.
- Browser
- Download file 2.89 GB
-
https://huggingface.co/Jieya/model_out_canny_captioned/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://Jieya/model_out_canny_captioned/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Jieya/model_out_canny_captioned/resolve/main/checkpoint-2000/optimizer.bin
2.89 GB
- Xet hash:
- 59ed8963f0f5ef0da83933f51f00ff01aca2a7d0f1ccc083828f19374430b555
- Size of remote file:
- 2.89 GB
- SHA256:
- e4205e07f45d3ca8f2a9bf17a45bde1191648fa23759cda56a66d9575eea8e23
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