Instructions to use cerspense/zeroscope_v1_320s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cerspense/zeroscope_v1_320s with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v1_320s", 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
- Xet hash:
- 2ef1f09e6e40fbe92a4dc716b74fa52d512f60df917495005c97e1b36c95ff00
- Size of remote file:
- 2.82 GB
- SHA256:
- 561f96bf406658431d281cacdd3bc3bafda9ea625e290b8268b299fb626c38b9
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