Instructions to use kebab111/Grapelike with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kebab111/Grapelike with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kebab111/Grapelike", 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 kebab111/Grapelike: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/kebab111/Grapelike/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://kebab111/Grapelike/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/kebab111/Grapelike/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- d8dbc920a078cdd1cd2d8cedc5f8b3239d1c1b887daf8c1143547f2b5cd3c902
- Size of remote file:
- 335 MB
- SHA256:
- b5e60c0250d0d1e8b0cbad73d25ba325d1bf4a04b8d6b67c0fd4ba6edb9f7bc7
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