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-3000/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-3000/optimizer.bin
- Command line
-
hf download hf://Jason248/newControlnet/checkpoint-3000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Jason248/newControlnet/resolve/main/checkpoint-3000/optimizer.bin
2.89 GB
- Xet hash:
- cd1d6f8ee2d606c6f31538bafba19bea0f487eb1c250d6e2d2eaab0009734f60
- Size of remote file:
- 2.89 GB
- SHA256:
- 19680ef2b1c17ae89d0d047934fe3f71652d221c57c5847d33e2e7bc8ff1197c
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