Instructions to use armwaheed/stable-diffusion-3.5-medium-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use armwaheed/stable-diffusion-3.5-medium-onnx with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("armwaheed/stable-diffusion-3.5-medium-onnx", 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_encoder/model.onnx from armwaheed/stable-diffusion-3.5-medium-onnx: direct link, hf CLI and curl.
- Browser
- Download file 137 MB
-
https://huggingface.co/armwaheed/stable-diffusion-3.5-medium-onnx/resolve/main/vae_encoder/model.onnx
- Command line
-
hf download hf://armwaheed/stable-diffusion-3.5-medium-onnx/vae_encoder/model.onnx
-
curl -L -o model.onnx https://huggingface.co/armwaheed/stable-diffusion-3.5-medium-onnx/resolve/main/vae_encoder/model.onnx
137 MB
- Xet hash:
- 6fc5fc270f01c7c6679efd5845eb0208cd10695e964c31f54160a8c49b34bc88
- Size of remote file:
- 137 MB
- SHA256:
- 8ee05f9461637a65cedd81dbe2c391b74e4d9d165233cdb20acd7046778acb3e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.