Instructions to use ddmlproject/cassianatuzzi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ddmlproject/cassianatuzzi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ddmlproject/cassianatuzzi", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 46f31c63a67e42d7b5e40db0f2b562f32631ef1847eb207d8c35d80c4289a310
- Size of remote file:
- 3.46 GB
- SHA256:
- 526b1366ac2b7bf637258471d2f69645c192938657a81b0fe9ad121d1ddc7991
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.