Instructions to use richiebailey/subpar7_sd15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use richiebailey/subpar7_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/subpar7_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 text_encoder/pytorch_model.bin from richiebailey/subpar7_sd15: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/richiebailey/subpar7_sd15/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://richiebailey/subpar7_sd15/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/richiebailey/subpar7_sd15/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 8b690fd0c168331235de6cefe520af736bbc3bd81511116b820db6a447196a39
- Size of remote file:
- 492 MB
- SHA256:
- bc816a8a089c2ebbd95106fbb610d5c89b0ccc52012a69fb32f45c38fa3447c1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.