Instructions to use Mark000111888/first with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mark000111888/first with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Mark000111888/first", 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
- Xet hash:
- 30cf2594c449025a7ddb8994b5ac10cd0d8edff6416cf214bdcd47ba63175d26
- Size of remote file:
- 246 MB
- SHA256:
- 5d04153ebb1d3af8de535362303946bedbeabfae01db3d7599d82b683cfa7685
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