Instructions to use ainz/diseny-pixar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ainz/diseny-pixar with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ainz/diseny-pixar", 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 ainz/diseny-pixar: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/ainz/diseny-pixar/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://ainz/diseny-pixar/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/ainz/diseny-pixar/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 1e271017e2601193b561e2692faf618952633a5318b8a89b3be6666df9f71263
- Size of remote file:
- 335 MB
- SHA256:
- 69050f162013ff9b33a58bf810d24bed45ca20519851638dabb3de9e50b2a6bf
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