Instructions to use julienkay/stable-diffusion-v1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use julienkay/stable-diffusion-v1-5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("julienkay/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae_decoder/model.onnx from julienkay/stable-diffusion-v1-5: direct link, hf CLI and curl.
- Browser
- Download file 198 MB
-
https://huggingface.co/julienkay/stable-diffusion-v1-5/resolve/main/vae_decoder/model.onnx
- Command line
-
hf download hf://julienkay/stable-diffusion-v1-5/vae_decoder/model.onnx
-
curl -L -o model.onnx https://huggingface.co/julienkay/stable-diffusion-v1-5/resolve/main/vae_decoder/model.onnx
198 MB
- Xet hash:
- dc729c7304d2a5a71ac13433a11f4bd4c7f43a089e09c160e500fba1aafad5ae
- Size of remote file:
- 198 MB
- SHA256:
- 500050d2dbd88e78f073d0a5bbd8100117886b1e2a7b160c29d373cd60fd08ce
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