Instructions to use emte/your-model-name with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use emte/your-model-name with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("emte/your-model-name", 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:
- 0d9381f01dbb07c41efa97f612082fc6c1503ce3f650092e02d9fb72d36cb328
- Size of remote file:
- 11.9 GB
- SHA256:
- 74a6b441747876391df8149541cf40c48fe5c9acf05d009480556390e6b36790
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