Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
diffusers-training
Instructions to use Jason248/newControlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jason248/newControlnet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Jason248/newControlnet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stable-diffusion-v1-5/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1500/optimizer.bin from Jason248/newControlnet: direct link, hf CLI and curl.
- Browser
- Download file 2.89 GB
-
https://huggingface.co/Jason248/newControlnet/resolve/main/checkpoint-1500/optimizer.bin
- Command line
-
hf download hf://Jason248/newControlnet/checkpoint-1500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Jason248/newControlnet/resolve/main/checkpoint-1500/optimizer.bin
2.89 GB
- Xet hash:
- 39f296c933dd63b949286b6781799eb8ec336196149f405f760430eb63b8a8ab
- Size of remote file:
- 2.89 GB
- SHA256:
- d08a4bcee18c1f186a0e660c2db0cda07bf4e42e50f6960abc5f618cb52ebffe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.