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:
- ead10f6f9c97375c7c39d0d75e09490bad6f83c77cd5851034921ac94e5c9fdb
- Size of remote file:
- 681 MB
- SHA256:
- 1de8688f0759d3faaac9857fca8a7568f784ea95931fc1170a0403cc4e15303f
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