Text-to-Image
Diffusers
Safetensors
stable-diffusion-xl
stable-diffusion-xl-diffusers
controlnet
diffusers-training
Instructions to use watsydney/result3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use watsydney/result3 with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("watsydney/result3") 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 watsydney/result3: direct link, hf CLI and curl.
- Browser
- Download file 2.51 GB
-
https://huggingface.co/watsydney/result3/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://watsydney/result3/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/watsydney/result3/resolve/main/checkpoint-2000/optimizer.bin
2.51 GB
- Xet hash:
- 496a07492f25b5e450b3782c8499a6bc755c7fc9129dbb11ed9b591509faed1c
- Size of remote file:
- 2.51 GB
- SHA256:
- 49f23bcc8d1530330b8a88cdf6fbc584474b196d9640751b7bbf062063d75107
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