Instructions to use keshan/controlnet_amateur_drawings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use keshan/controlnet_amateur_drawings with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("keshan/controlnet_amateur_drawings") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download 85000/diffusion_flax_model.msgpack from keshan/controlnet_amateur_drawings: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/keshan/controlnet_amateur_drawings/resolve/main/85000/diffusion_flax_model.msgpack
- Command line
-
hf download hf://keshan/controlnet_amateur_drawings/85000/diffusion_flax_model.msgpack
-
curl -L -o diffusion_flax_model.msgpack https://huggingface.co/keshan/controlnet_amateur_drawings/resolve/main/85000/diffusion_flax_model.msgpack
1.45 GB
- Xet hash:
- 0d760ba372716a2add40dd6ef1d8e7b2efeb5a7dec6e55cd3450fab32396241f
- Size of remote file:
- 1.45 GB
- SHA256:
- 21dc45506a10e9cbfe9511a96536abbb20dcef2017f6263736833882938145f3
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