Instructions to use SkyworkAIGC/SkyPaint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SkyworkAIGC/SkyPaint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SkyworkAIGC/SkyPaint", 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 SkyworkAIGC/SkyPaint: direct link, hf CLI and curl.
- Browser
- Download file 666 MB
-
https://huggingface.co/SkyworkAIGC/SkyPaint/resolve/refs%2Fpr%2F3/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://SkyworkAIGC/SkyPaint@refs/pr/3/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SkyworkAIGC/SkyPaint/resolve/refs%2Fpr%2F3/text_encoder/pytorch_model.bin
666 MB
- Xet hash:
- d6a0bdb50deb2e5860d5b7894919d6251c8e928e6ca160145246f9dd5d2b112d
- Size of remote file:
- 666 MB
- SHA256:
- 36e89fbaeac21c93a0b57fa0cefaad5eb4224c75ee85c9c43b33461fe3239f52
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.