Instructions to use johnowhitaker/rainbowdiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use johnowhitaker/rainbowdiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("johnowhitaker/rainbowdiffusion", 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 johnowhitaker/rainbowdiffusion: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/johnowhitaker/rainbowdiffusion/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://johnowhitaker/rainbowdiffusion/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/johnowhitaker/rainbowdiffusion/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- aad0444a4083a796626ca1abf4b9bae457b0d9ca3e22aa2dd092c2c3510904b7
- Size of remote file:
- 492 MB
- SHA256:
- 4e0dd6030b5285f0da259ac5a30b8456cc86f92e7d22112e712050e196da7f14
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