Instructions to use richiebailey/subpar3_sd15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use richiebailey/subpar3_sd15 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("richiebailey/subpar3_sd15", 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/diffusion_pytorch_model.bin from richiebailey/subpar3_sd15: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/richiebailey/subpar3_sd15/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://richiebailey/subpar3_sd15/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/richiebailey/subpar3_sd15/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- b2432acb68ed3c541679f9fc583f4be6d92682901be06c293d7037739be35689
- Size of remote file:
- 335 MB
- SHA256:
- 89b90423c75f3fc58d8fe27f87a2a182a13a6d4509d07abe3e1dcef76241fac0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.