Instructions to use kmaksatk/controlnet_80k_data_blip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kmaksatk/controlnet_80k_data_blip with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("kmaksatk/controlnet_80k_data_blip") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Ctrl+K
- checkpoint-10000
- checkpoint-15000
- checkpoint-20000
- checkpoint-25000
- checkpoint-30000
- checkpoint-35000
- checkpoint-40000
- checkpoint-45000
- checkpoint-5000
- checkpoint-50000
- checkpoint-55000
- checkpoint-60000
- checkpoint-65000
- checkpoint-70000
- checkpoint-75000
- checkpoint-80000
- 1.67 kB
- 732 Bytes
- 1.29 kB
- 1.45 GB xet
- 29.3 kB
- 1.51 MB xet
- 1.36 MB xet
- 1.39 MB xet