Instructions to use fusing/sd-image-variations-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fusing/sd-image-variations-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fusing/sd-image-variations-diffusers", 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
Download vae/diffusion_pytorch_model.bin from fusing/sd-image-variations-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/fusing/sd-image-variations-diffusers/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://fusing/sd-image-variations-diffusers/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/fusing/sd-image-variations-diffusers/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- bc0a5b1a4fb1ab8645861ed38644f72bb3853ace719396dd1df938220c411365
- Size of remote file:
- 335 MB
- SHA256:
- f506c519bca6fcb25f695b94364422f7b2f534d52ded3decbcd6674a5101b500
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