Instructions to use Mark000111888/second with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mark000111888/second 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/second", 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:
- 7267e56f09e86f77726e1d152c4a6fd112a4f4ec191174a8a15a14fc81b369d6
- Size of remote file:
- 2.13 GB
- SHA256:
- 043cb98fad6961d66500da97ad557a19bdda5235e97ac11f7656c99436f69a3e
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