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-2000/random_states_0.pkl from Jason248/newControlnet: direct link, hf CLI and curl.
- Browser
- Download file 14.4 kB
-
https://huggingface.co/Jason248/newControlnet/resolve/main/checkpoint-2000/random_states_0.pkl
- Command line
-
hf download hf://Jason248/newControlnet/checkpoint-2000/random_states_0.pkl
-
curl -L -o random_states_0.pkl https://huggingface.co/Jason248/newControlnet/resolve/main/checkpoint-2000/random_states_0.pkl
14.4 kB
- Xet hash:
- ed29ea258cbb44106196738e81a85542f2ad291571811a3224b06c8b4d65c47c
- Size of remote file:
- 14.4 kB
- SHA256:
- 033df8a3a5fea771dc560abcfe4087a9047cd7bc5de286671c82b0b397fac0d0
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