Instructions to use Learner/jax-diffuser-event with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Learner/jax-diffuser-event with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Learner/jax-diffuser-event") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download diffusion_pytorch_model.fp16.safetensors from Learner/jax-diffuser-event: direct link, hf CLI and curl.
- Browser
- Download file 723 MB
-
https://huggingface.co/Learner/jax-diffuser-event/resolve/main/diffusion_pytorch_model.fp16.safetensors
- Command line
-
hf download hf://Learner/jax-diffuser-event/diffusion_pytorch_model.fp16.safetensors
-
curl -L -o diffusion_pytorch_model.fp16.safetensors https://huggingface.co/Learner/jax-diffuser-event/resolve/main/diffusion_pytorch_model.fp16.safetensors
723 MB
- Xet hash:
- 9e1f006aa6e33c963a9ab57691636561112297cbb30dbc945991d1a0541212fb
- Size of remote file:
- 723 MB
- SHA256:
- 680ef33221ddbbe524f906d126b34d4f7910102f263b703e78fd8360ebc10bed
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